Exploring an Ecologically Sustainable Scheme for Landscape Restoration of Abandoned Mine Land: Scenario-Based Simulation Integrated Linear Programming and CLUE-S Model.

PubMed

Zhang, Liping; Zhang, Shiwen; Huang, Yajie; Cao, Meng; Huang, Yuanfang; Zhang, Hongyan

2016-03-24

Understanding abandoned mine land (AML) changes during land reclamation is crucial for reusing damaged land resources and formulating sound ecological restoration policies. This study combines the linear programming (LP) model and the CLUE-S model to simulate land-use dynamics in the Mentougou District (Beijing, China) from 2007 to 2020 under three reclamation scenarios, that is, the planning scenario based on the general land-use plan in study area (scenario 1), maximal comprehensive benefits (scenario 2), and maximal ecosystem service value (scenario 3). Nine landscape-scale graph metrics were then selected to describe the landscape characteristics. The results show that the coupled model presented can simulate the dynamics of AML effectively and the spatially explicit transformations of AML were different. New cultivated land dominates in scenario 1, while construction land and forest land account for major percentages in scenarios 2 and 3, respectively. Scenario 3 has an advantage in most of the selected indices as the patches combined most closely. To conclude, reclaiming AML by transformation into more forest can reduce the variability and maintain the stability of the landscape ecological system in study area. These findings contribute to better mapping AML dynamics and providing policy support for the management of AML.

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.

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.

Mapping Multi-Cropped Land Use to Estimate Water Demand Using the California Pesticide Reporting Database

NASA Astrophysics Data System (ADS)

Henson, W.; Baillie, M. N.; Martin, D.

2017-12-01

Detailed and dynamic land-use data is one of the biggest data deficiencies facing food and water security issues. Better land-use data results in improved integrated hydrologic models that are needed to look at the feedback between land and water use, specifically for adequately representing changes and dynamics in rainfall-runoff, urban and agricultural water demands, and surface fluxes of water (e.g., evapotranspiration, runoff, and infiltration). Currently, land-use data typically are compiled from annual (e.g., Crop Scape) or multi-year composites if mapped at all. While this approach provides information about interannual land-use practices, it does not capture the dynamic changes in highly developed agricultural lands prevalent in California agriculture such as (1) dynamic land-use changes from high frequency multi-crop rotations and (2) uncertainty in sub-annual crop distribution, planting times, and cropped areas. California has collected spatially distributed data for agricultural pesticide use since 1974 through the California Pesticide Information Portal (CalPIP). A method leveraging the CalPIP database has been developed to provide vital information about dynamic agricultural land use (e.g., crop distribution and planting times) and water demand issues in Salinas Valley, California, along the central coast. This 7 billion dollar/year agricultural area produces up to 50% of U.S. lettuce and broccoli. Therefore, effective and sustainable water resource development in the area must balance the needs of this essential industry, other beneficial uses, and the environment. This new tool provides a way to provide more dynamic crop data in hydrologic models. While the current application focuses on the Salinas Valley, the methods are extensible to all of California and other states with similar pesticide reporting. The improvements in representing variability in crop patterns and associated water demands increase our understanding of land-use change and precision of hydrologic decision models. Ultimately, further refinement to the parcel level will completely capture the changing topology of agricultural land use.

Land use, water and Mediterranean landscapes: modelling long-term dynamics of complex socio-ecological systems.

PubMed

Barton, C Michael; Ullah, Isaac I; Bergin, Sean

2010-11-28

The evolution of Mediterranean landscapes during the Holocene has been increasingly governed by the complex interactions of water and human land use. Different land-use practices change the amount of water flowing across the surface and infiltrating the soil, and change water's ability to move surface sediments. Conversely, water amplifies the impacts of human land use and extends the ecological footprint of human activities far beyond the borders of towns and fields. Advances in computational modelling offer new tools to study the complex feedbacks between land use, land cover, topography and surface water. The Mediterranean Landscape Dynamics project (MedLand) is building a modelling laboratory where experiments can be carried out on the long-term impacts of agropastoral land use, and whose results can be tested against the archaeological record. These computational experiments are providing new insights into the socio-ecological consequences of human decisions at varying temporal and spatial scales.

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.

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.

Astronaut Risk Levels During Crew Module (CM) Land Landing

NASA Technical Reports Server (NTRS)

Lawrence, Charles; Carney, Kelly S.; Littell, Justin

2007-01-01

The NASA Engineering Safety Center (NESC) is investigating the merits of water and land landings for the crew exploration vehicle (CEV). The merits of these two options are being studied in terms of cost and risk to the astronauts, vehicle, support personnel, and general public. The objective of the present work is to determine the astronaut dynamic response index (DRI), which measures injury risks. Risks are determined for a range of vertical and horizontal landing velocities. A structural model of the crew module (CM) is developed and computational simulations are performed using a transient dynamic simulation analysis code (LS-DYNA) to determine acceleration profiles. Landing acceleration profiles are input in a human factors model that determines astronaut risk levels. Details of the modeling approach, the resulting accelerations, and astronaut risk levels are provided.

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.

Nutrient cycle benchmarks for earth system land model

NASA Astrophysics Data System (ADS)

Zhu, Q.; Riley, W. J.; Tang, J.; Zhao, L.

2017-12-01

Projecting future biosphere-climate feedbacks using Earth system models (ESMs) relies heavily on robust modeling of land surface carbon dynamics. More importantly, soil nutrient (particularly, nitrogen (N) and phosphorus (P)) dynamics strongly modulate carbon dynamics, such as plant sequestration of atmospheric CO2. Prevailing ESM land models all consider nitrogen as a potentially limiting nutrient, and several consider phosphorus. However, including nutrient cycle processes in ESM land models potentially introduces large uncertainties that could be identified and addressed by improved observational constraints. We describe the development of two nutrient cycle benchmarks for ESM land models: (1) nutrient partitioning between plants and soil microbes inferred from 15N and 33P tracers studies and (2) nutrient limitation effects on carbon cycle informed by long-term fertilization experiments. We used these benchmarks to evaluate critical hypotheses regarding nutrient cycling and their representation in ESMs. We found that a mechanistic representation of plant-microbe nutrient competition based on relevant functional traits best reproduced observed plant-microbe nutrient partitioning. We also found that for multiple-nutrient models (i.e., N and P), application of Liebig's law of the minimum is often inaccurate. Rather, the Multiple Nutrient Limitation (MNL) concept better reproduces observed carbon-nutrient interactions.

The effects of changing land cover on streamflow simulation in Puerto Rico

USGS Publications Warehouse

Van Beusekom, Ashley E.; Hay, Lauren E.; Viger, Roland; Gould, William A.; Collazo, Jaime; Henareh Khalyani, Azad

2014-01-01

This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from four land cover scenes for the period 1953-2012. The PRMS simulations based on static land cover illustrated consistent differences in simulated streamflow across the island. It was determined that the scale of the analysis makes a difference: large regions with localized areas that have undergone dramatic land cover change may show negligible difference in total streamflow, but streamflow simulations using dynamic land cover parameters for a highly altered subwatershed clearly demonstrate the effects of changing land cover on simulated streamflow. Incorporating dynamic parameterization in these highly altered watersheds can reduce the predictive uncertainty in simulations of streamflow using PRMS. Hydrologic models that do not consider the projected changes in land cover may be inadequate for water resource management planning for future conditions.

Application research on land use remote sensing dynamic monitoring: A case study of Anning district, Lanzhou

NASA Astrophysics Data System (ADS)

Zhu, Yunqiang; Zhu, Huazhong; Lu, Heli; Ni, Jianguang; Zhu, Shaoxia

2005-10-01

Remote sensing dynamic monitoring of land use can detect the change information of land use and update the current land use map, which is important for rational utilization and scientific management of land resources. This paper discusses the technological procedure of remote sensing dynamic monitoring of land use including the process of remote sensing images, the extraction of annual change information of land use, field survey, indoor post processing and accuracy assessment. Especially, we emphasize on comparative research on the choice of remote sensing rectifying models, image fusion algorithms and accuracy assessment methods. Taking Anning district in Lanzhou as an example, we extract the land use change information of the district during 2002-2003, access monitoring accuracy and analyze the reason of land use change.

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.

Dynamic modeling of Tampa Bay urban development using parallel computing

USGS Publications Warehouse

Xian, G.; Crane, M.; Steinwand, D.

2005-01-01

Urban land use and land cover has changed significantly in the environs of Tampa Bay, Florida, over the past 50 years. Extensive urbanization has created substantial change to the region's landscape and ecosystems. This paper uses a dynamic urban-growth model, SLEUTH, which applies six geospatial data themes (slope, land use, exclusion, urban extent, transportation, hillside), to study the process of urbanization and associated land use and land cover change in the Tampa Bay area. To reduce processing time and complete the modeling process within an acceptable period, the model is recoded and ported to a Beowulf cluster. The parallel-processing computer system accomplishes the massive amount of computation the modeling simulation requires. SLEUTH calibration process for the Tampa Bay urban growth simulation spends only 10 h CPU time. The model predicts future land use/cover change trends for Tampa Bay from 1992 to 2025. Urban extent is predicted to double in the Tampa Bay watershed between 1992 and 2025. Results show an upward trend of urbanization at the expense of a decline of 58% and 80% in agriculture and forested lands, respectively.

Simulation of Land-Cover Change in Taipei Metropolitan Area under Climate Change Impact

NASA Astrophysics Data System (ADS)

Huang, Kuo-Ching; Huang, Thomas C. C.

2014-02-01

Climate change causes environment change and shows up on land covers. Through observing the change of land use, researchers can find out the trend and potential mechanism of the land cover change. Effective adaptation policies can affect pattern of land cover change and may decrease the risks of climate change impacts. By simulating land use dynamics with scenario settings, this paper attempts to explore the relationship between climate change and land-cover change through efficient adaptation polices. It involves spatial statistical model in estimating possibility of land-cover change, cellular automata model in modeling land-cover dynamics, and scenario analysis in response to adaptation polices. The results show that, without any control, the critical eco-areas, such as estuarine areas, will be destroyed and people may move to the vulnerable and important economic development areas. In the other hand, under the limited development condition for adaptation, people migration to peri-urban and critical eco-areas may be deterred.

Diagnosing the influence of model structure on the simulation of water, energy and carbon fluxes on bark beetle infested forests

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Gutmann, E. D.; Brooks, P. D.; Reed, D. E.; Ewers, B. E.; Pendall, E.; Biederman, J. A.; Harpold, A. A.; Barnard, H. R.; Hu, J.

2011-12-01

Forest dynamics induced by insect infestation can have a significant, local impact on plant physiological regulation of water, energy and carbon fluxes. Rapid mortality succeeded by more gradually varying land cover changes are presently thought to initiate a cascade of changes to water, energy and carbon budgets at the forest stand scale. Initial model sensitivity results have suggested very strong changes in land-atmosphere exchanges of these variables. Specifically, model results from the Noah land surface model, a relatively simple model, have suggested that loss of transpiration function may result in a nearly 50% increase in seasonal soil moisture values and similar increases in runoff production for locations in the central Rocky Mountains. However, differing model structures, such as the representation of plant canopy architecture, snowpack dynamics, dynamic vegetation and hillslope hydrologic processes, may significantly confound the synthesis of results from different modeling systems. We assess the performance of new suite of model simulations from three different land surface models of differing model structures and complexity levels against a comprehensive set of field observations of land surface flux and state variables. The focus of the analysis is in diagnosing how model structure influences changes in energy, water and carbon budget partitioning prior to and following insect infestation. Specific emphasis in this presentation is placed on verifying variables that characterize top of canopy and within canopy energy and water fluxes. We conclude the presentation with a set of recommendations about the advantages and disadvantages of various model structures in their simulation of insect driven forest dynamics.

Modeling the influence of long term human-induced land use conversion on sediment fluxes and carbon dynamics at the catchment scale

NASA Astrophysics Data System (ADS)

Bouchoms, Samuel; Van Oost, Kristof; Vanacker, Veerle

2014-05-01

Over the past 20 years, there has been increasing evidence of the strong impact of human activities on the landscape, specifically on soil erosion due to the removal of natural vegetation cover for agricultural and urban purposes. The results question the widespread hypothesis of a steady state landscape since it appears that the balance between soil production and erosion may be broken altering the interactions between chemical, physical and biological processes in both soil and landscape system. Yet, the relationship between this accelerated erosion and the carbon dynamics at the landscape scale remains an important area of investigation. Recent attempts to combine geomorphic models, soil redistribution and carbon dynamic has proved themselves valuable in term of supporting the importance of lateral fluxes as a crucial control of carbon dynamic at the landscape scale. We use the SPEROS LT model, a modified version of SPEROS-C which includes dynamic land use and soil physical properties, to assess the impact of historical land use conversion on sediment and carbon fluxes in the Dijle catchment. This particular location has experienced a significant human impact since the Roman period, undergoing heavy deforestation and expansion of agricultural lands followed by a period of abandonment. The last 400 to 500 years saw a dramatic increase in the intensity of land use conversion associated to population growth leading to forest cleaning and urbanization. Our main objective is to validate the combined geomorphic and soil carbon turnover process descriptions of the model. Historical land use proportions are based on existing literature estimations and spatial assignation of the land conversion relies on simple allocation rules based on criteria such as slope or soil texture. Land use scenarios are constructed for the last 2000 years. We confront the model results with observations and perform a sensitivity analysis. The results indicate that the general trends in sediment production and deposition, as well as soil carbon storage are well predicted by the model. We discuss the key-parameters of the model and the implications of past erosion-deposition for the future C budget of the Dijle catchment.

A Mathematical Model for Vertical Attitude Takeoff and Landing (VATOL) Aircraft Simulation. Volume 1; Model Description Application

NASA Technical Reports Server (NTRS)

Fortenbaugh, R. L.

1980-01-01

A mathematical model of a high performance airplane capable of vertical attitude takeoff and landing (VATOL) was developed. An off line digital simulation program incorporating this model was developed to provide trim conditions and dynamic check runs for the piloted simulation studies and support dynamic analyses of proposed VATOL configuration and flight control concepts. Development details for the various simulation component models and the application of the off line simulation program, Vertical Attitude Take-Off and Landing Simulation (VATLAS), to develop a baseline control system for the Vought SF-121 VATOL airplane concept are described.

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.

Understanding the Dynamics of Socio-Hydrological Environment: a Conceptual Framework

NASA Astrophysics Data System (ADS)

Woyessa, Y.; Welderufael, W.; Edossa, D.

2011-12-01

Human actions affect ecological systems and the services they provide through various activities, such as land use, water use, pollution and climate change. Climate change is perhaps one of the most important sustainable development challenges that threaten to undo many of the development efforts being made to reach the targets set for the Millennium Development Goals. Understanding the change of ecosystems under different scenarios of climate and biophysical conditions could assist in bringing the issue of ecosystem services into decision making process. Similarly, the impacts of land use change on ecosystems and biodiversity have received considerable attention from ecologists and hydrologists alike. Land use change in a catchment can impact on water supply by altering hydrological processes, such as infiltration, groundwater recharge, base flow and direct runoff. In the past a variety of models were used for predicting land-use changes. Recently the focus has shifted away from using mathematically oriented models to agent-based modelling (ABM) approach to simulate land use scenarios. A conceptual framework is being developed which integrates climate change scenarios and the human dimension of land use decision into a hydrological model in order to assess its impacts on the socio-hydrological dynamics of a river basin. The following figures present the framework for the analysis and modelling of the socio-hydrological dynamics. Keywords: climate change, land use, river basin

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

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

A socio-hydrologic model of coupled water-agriculture dynamics with emphasis on farm size.

NASA Astrophysics Data System (ADS)

Brugger, D. R.; Maneta, M. P.

2015-12-01

Agricultural land cover dynamics in the U.S. are dominated by two trends: 1) total agricultural land is decreasing and 2) average farm size is increasing. These trends have important implications for the future of water resources because 1) growing more food on less land is due in large part to increased groundwater withdrawal and 2) larger farms can better afford both more efficient irrigation and more groundwater access. However, these large-scale trends are due to individual farm operators responding to many factors including climate, economics, and policy. It is therefore difficult to incorporate the trends into watershed-scale hydrologic models. Traditional scenario-based approaches are valuable for many applications, but there is typically no feedback between the hydrologic model and the agricultural dynamics and so limited insight is gained into the how agriculture co-evolves with water resources. We present a socio-hydrologic model that couples simplified hydrologic and agricultural economic dynamics, accounting for many factors that depend on farm size such as irrigation efficiency and returns to scale. We introduce an "economic memory" (EM) state variable that is driven by agricultural revenue and affects whether farms are sold when land market values exceed expected returns from agriculture. The model uses a Generalized Mixture Model of Gaussians to approximate the distribution of farm sizes in a study area, effectively lumping farms into "small," "medium," and "large" groups that have independent parameterizations. We apply the model in a semi-arid watershed in the upper Columbia River Basin, calibrating to data on streamflow, total agricultural land cover, and farm size distribution. The model is used to investigate the sensitivity of the coupled system to various hydrologic and economic scenarios such as increasing market value of land, reduced surface water availability, and increased irrigation efficiency in small farms.

Impacts of land cover data selection and trait parameterisation on dynamic modelling of species' range expansion.

PubMed

Heikkinen, Risto K; Bocedi, Greta; Kuussaari, Mikko; Heliölä, Janne; Leikola, Niko; Pöyry, Juha; Travis, Justin M J

2014-01-01

Dynamic models for range expansion provide a promising tool for assessing species' capacity to respond to climate change by shifting their ranges to new areas. However, these models include a number of uncertainties which may affect how successfully they can be applied to climate change oriented conservation planning. We used RangeShifter, a novel dynamic and individual-based modelling platform, to study two potential sources of such uncertainties: the selection of land cover data and the parameterization of key life-history traits. As an example, we modelled the range expansion dynamics of two butterfly species, one habitat specialist (Maniola jurtina) and one generalist (Issoria lathonia). Our results show that projections of total population size, number of occupied grid cells and the mean maximal latitudinal range shift were all clearly dependent on the choice made between using CORINE land cover data vs. using more detailed grassland data from three alternative national databases. Range expansion was also sensitive to the parameterization of the four considered life-history traits (magnitude and probability of long-distance dispersal events, population growth rate and carrying capacity), with carrying capacity and magnitude of long-distance dispersal showing the strongest effect. Our results highlight the sensitivity of dynamic species population models to the selection of existing land cover data and to uncertainty in the model parameters and indicate that these need to be carefully evaluated before the models are applied to conservation planning.

Degradation dynamics and bioavailability of land-based dissolved organic nitrogen in the Bohai Sea: Linking experiment with modeling.

PubMed

Li, Keqiang; Ma, Yunpeng; Dai, Aiquan; Wang, Xiulin

2017-11-30

Dissolved organic nitrogen (DON) is the major nitrogen form in the Bohai Sea. Land-based DON is released into the nitrogen pool and degraded by planktonic microbiota in coastal ocean. In this study, we evaluated the degradation of land-based DON, particularly its dynamics and bioavailability, in coastal water by linking experiment and modeling. Results showed that the degradation rate constant of DON from sewage treatment plant was significantly faster than those of other land-based sources (P<0.05). DON was classified into three categories based on dynamics and bioavailability. The supply of dissolved inorganic nitrogen (DIN) pool from the DON pool of Liao River, Hai River, and Yellow River was explored using a 3D hydrodynamic multi-DON biogeochemical model in the Bohai Sea. In the model, large amounts of DIN were supplied from DON of Liao River than the other rivers because of prolonged flushing time in Liaodong Bay. Copyright © 2017 Elsevier Ltd. All rights reserved.

Orbiter Landing Loads Math Model Description and Correlation with ALT Flight Data

NASA Technical Reports Server (NTRS)

Hamilton, D. A.; Schliesing, J. A.; Zupp, G. A., Jr.

1980-01-01

Results of the space shuttle approach and landing test are examined in order to assess landing gear characteristics and performance and verify landing dynamic analyses. The landing gears were instrumented with load-calibrated strain gages, a wheel-speed sensor, and strut stroke measurement devices. The mathematical procedure used in predicting the shuttle touchdown loads and dynamics is presented together with the comparisons between measured flight data and the analytical predictions. Conclusions from these data are also presented.

Carbon cycling under 300 years of land use change: importance of the secondary vegetation sink

USGS Publications Warehouse

Shevliakova, Elena; Pacala, Stephen W.; Malyshev, Sergey; Hurtt, George C.; Milly, P.C.D.; Caspersen, John P.; Sentman, Lori T.; Fisk, Justin P.; Wirth, Christian; Crevoisier, Cyril

2009-01-01

We have developed a dynamic land model (LM3V) able to simulate ecosystem dynamics and exchanges of water, energy, and CO2 between land and atmosphere. LM3V is specifically designed to address the consequences of land use and land management changes including cropland and pasture dynamics, shifting cultivation, logging, fire, and resulting patterns of secondary regrowth. Here we analyze the behavior of LM3V, forced with the output from the Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric model AM2, observed precipitation data, and four historic scenarios of land use change for 1700-2000. Our analysis suggests a net terrestrial carbon source due to land use activities from 1.1 to 1.3 GtC/a during the 1990s, where the range is due to the difference in the historic cropland distribution. This magnitude is substantially smaller than previous estimates from other models, largely due to our estimates of a secondary vegetation sink of 0.35 to 0.6 GtC/a in the 1990s and decelerating agricultural land clearing since the 1960s. For the 1990s, our estimates for the pastures' carbon flux vary from a source of 0.37 to a sink of 0.15 GtC/a, and for the croplands our model shows a carbon source of 0.6 to 0.9 GtC/a. Our process-based model suggests a smaller net deforestation source than earlier bookkeeping models because it accounts for decelerated net conversion of primary forest to agriculture and for stronger secondary vegetation regrowth in tropical regions. The overall uncertainty is likely to be higher than the range reported here because of uncertainty in the biomass recovery under changing ambient conditions, including atmospheric CO2 concentration, nutrients availability, and climate. Copyright 2009 by the American Geophysical Union.

Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

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

Yu, Miao; Wang, Guiling; Chen, Haishan

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to be seen in the Northern Hemisphere high latitudes. Including representation of vegetation dynamics is expected to further amplify the model-related uncertainties in projected future changes in surface water and heat fluxes as well as soil moisture content. This is especially the case in the high latitudes of the Northern Hemisphere (e.g., northwestern North America and central North Asia) where the projected vegetation changes are uncertain and in the Tropics (e.g., the Amazon and Congo Basins) where dense vegetation exists. Finally, findings from this study highlight the importance of improving land surface model parameterizations related to soil and snow processes, as well as the importance of improving the accuracy of dynamic vegetation models.« less

Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

DOE PAGES

Yu, Miao; Wang, Guiling; Chen, Haishan

2016-03-01

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to be seen in the Northern Hemisphere high latitudes. Including representation of vegetation dynamics is expected to further amplify the model-related uncertainties in projected future changes in surface water and heat fluxes as well as soil moisture content. This is especially the case in the high latitudes of the Northern Hemisphere (e.g., northwestern North America and central North Asia) where the projected vegetation changes are uncertain and in the Tropics (e.g., the Amazon and Congo Basins) where dense vegetation exists. Finally, findings from this study highlight the importance of improving land surface model parameterizations related to soil and snow processes, as well as the importance of improving the accuracy of dynamic vegetation models.« less

The topology of non-linear global carbon dynamics: from tipping points to planetary boundaries

NASA Astrophysics Data System (ADS)

Anderies, J. M.; Carpenter, S. R.; Steffen, Will; Rockström, Johan

2013-12-01

We present a minimal model of land use and carbon cycle dynamics and use it to explore the relationship between non-linear dynamics and planetary boundaries. Only the most basic interactions between land cover and terrestrial, atmospheric, and marine carbon stocks are considered in the model. Our goal is not to predict global carbon dynamics as it occurs in the actual Earth System. Rather, we construct a conceptually reasonable heuristic model of a feedback system between different carbon stocks that captures the qualitative features of the actual Earth System and use it to explore the topology of the boundaries of what can be called a ‘safe operating space’ for humans. The model analysis illustrates the existence of dynamic, non-linear tipping points in carbon cycle dynamics and the potential complexity of planetary boundaries. Finally, we use the model to illustrate some challenges associated with navigating planetary boundaries.

The AgroEcoSystem (AgES) response-function model simulates layered soil water dynamics in semi-arid Colorado: sensitivity and calibration

USDA-ARS?s Scientific Manuscript database

Simulation of vertical soil hydrology is a critical component of simulating even more complex soil water dynamics in space and time, including land-atmosphere and subsurface interactions. The AgroEcoSystem (AgES) model is defined here as a single land unit implementation of the full AgES-W (Watershe...

An integrated land change model for projecting future climate and land change scenarios

USGS Publications Warehouse

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

2013-01-01

Climate change will have myriad effects on ecosystems worldwide, and natural and anthropogenic disturbances will be key drivers of these dynamics. In addition to climatic effects, continual expansion of human settlement into fire-prone forests will alter fire regimes, increase human vulnerability, and constrain future forest management options. There is a need for modeling tools to support the simulation and assessment of new management strategies over large regions in the context of changing climate, shifting development patterns, and an expanding wildland-urban interface. To address this need, we developed a prototype land change simulator that combines human-driven land use change (derived from the FORE-SCE model) with natural disturbances and vegetation dynamics (derived from the LADS model) and incorporates novel feedbacks between human land use and disturbance regimes. The prototype model was implemented in a test region encompassing the Denver metropolitan area along with its surrounding forested and agricultural landscapes. Initial results document the feasibility of integrated land change modeling at a regional scale but also highlighted conceptual and technical challenges for this type of model integration. Ongoing development will focus on improving climate sensitivities and modeling constraints imposed by climate change and human population growth on forest management activities.

Estimating ecosystem carbon change in the Conterminous United States based on 40 years of land-use change and disturbance

NASA Astrophysics Data System (ADS)

Sleeter, B. M.; Rayfield, B.; Liu, J.; Sherba, J.; Daniel, C.; Frid, L.; Wilson, T. S.; Zhu, Z.

2016-12-01

Since 1970, the combined changes in land use, land management, climate, and natural disturbances have dramatically altered land cover in the United States, resulting in the potential for significant changes in terrestrial carbon storage and flux between ecosystems and the atmosphere. Processes including urbanization, agricultural expansion and contraction, and forest management have had impacts - both positive and negative - on the amount of natural vegetation, the age structure of forests, and the amount of impervious cover. Anthropogenic change coupled with climate-driven changes in natural disturbance regimes, particularly the frequency and severity of wildfire, together determine the spatio-temporal patterns of land change and contribute to changing ecosystem carbon dynamics. Quantifying this effect and its associated uncertainties is fundamental to developing a rigorous and transparent carbon monitoring and assessment programs. However, large-scale systematic inventories of historical land change and their associated uncertainties are sparse. To address this need, we present a newly developed modeling framework, the Land Use and Carbon Scenario Simulator (LUCAS). The LUCAS model integrates readily available high quality, empirical land-change data into a stochastic space-time simulation model representing land change feedbacks on carbon cycling in terrestrial ecosystems. We applied the LUCAS model to estimate regional scale changes in carbon storage, atmospheric flux, and net biome production in 84 ecological regions of the conterminous United States for the period 1970-2015. The model was parameterized using a newly available set of high resolution (30 m) land-change data, compiled from Landsat remote sensing imagery, including estimates of uncertainty. Carbon flux parameters for each ecological region were derived from the IBIS dynamic global vegetation model with full carbon cycle accounting. This paper presents our initial findings describing regional and temporal changes and variability in carbon storage and flux resulting from land use change and disturbance between 1973 and 2015. Additionally, based on stochastic simulations we quantify and present key sources of uncertainty in the estimation of terrestrial ecosystem carbon dynamics.

Application of tire dynamics to aircraft landing gear design analysis

NASA Technical Reports Server (NTRS)

Black, R. J.

1983-01-01

The tire plays a key part in many analyses used for design of aircraft landing gear. Examples include structural design of wheels, landing gear shimmy, brake whirl, chatter and squeal, complex combination of chatter and shimmy on main landing gear (MLG) systems, anti-skid performance, gear walk, and rough terrain loads and performance. Tire parameters needed in the various analyses are discussed. Two tire models are discussed for shimmy analysis, the modified Moreland approach and the von Schlippe-Dietrich approach. It is shown that the Moreland model can be derived from the Von Schlippe-Dietrich model by certain approximations. The remaining analysis areas are discussed in general terms and the tire parameters needed for each are identified. Accurate tire data allows more accurate design analysis and the correct prediction of dynamic performance of aircraft landing gear.

Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media.

PubMed

Sonter, Laura J; Watson, Keri B; Wood, Spencer A; Ricketts, Taylor H

2016-01-01

Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18-20.2 at 95% confidence) to Vermont's tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making.

Modelling the effect of urbanization on the transmission of an infectious disease.

PubMed

Zhang, Ping; Atkinson, Peter M

2008-01-01

This paper models the impact of urbanization on infectious disease transmission by integrating a CA land use development model, population projection matrix model and CA epidemic model in S-Plus. The innovative feature of this model lies in both its explicit treatment of spatial land use development, demographic changes, infectious disease transmission and their combination in a dynamic, stochastic model. Heuristically-defined transition rules in cellular automata (CA) were used to capture the processes of both land use development with urban sprawl and infectious disease transmission. A population surface model and dwelling distribution surface were used to bridge the gap between urbanization and infectious disease transmission. A case study is presented involving modelling influenza transmission in Southampton, a dynamically evolving city in the UK. The simulation results for Southampton over a 30-year period show that the pattern of the average number of infection cases per day can depend on land use and demographic changes. The modelling framework presents a useful tool that may be of use in planning applications.

Simulating land-atmosphere feedbacks and response to widespread forest disturbance: The role of lower boundary configuration and dynamic water table in meteorological modeling

NASA Astrophysics Data System (ADS)

Forrester, M.; Maxwell, R. M.; Bearup, L. A.; Gochis, D.

2017-12-01

Numerical meteorological models are frequently used to diagnose land-atmosphere interactions and predict large-scale response to extreme or hazardous events, including widespread land disturbance or perturbations to near-surface moisture. However, few atmospheric modeling platforms consider the impact that dynamic groundwater storage, specifically 3D subsurface flow, has on land-atmosphere interactions. In this study, we use the Weather Research and Forecasting (WRF) mesoscale meteorological model to identify ecohydrologic and land-atmosphere feedbacks to disturbance by the mountain pine beetle (MPB) over the Colorado Headwaters region. Disturbance simulations are applied to WRF with various lower boundary configurations: Including default Noah land surface model soil moisture representation; a version of WRF coupled to ParFlow (PF), an integrated groundwater-surface water model that resolves variably saturated flow in the subsurface; and WRF coupled to PF in a static water table version, simulating only vertical and no lateral subsurface flow. Our results agree with previous literature showing MPB-induced reductions in canopy transpiration in all lower boundary scenarios, as well as energy repartitioning, higher water tables, and higher planetary boundary layer over infested regions. Simulations show that expanding from local to watershed scale results in significant damping of MPB signal as unforested and unimpacted regions are added; and, while deforestation appears to have secondary feedbacks to planetary boundary layer and convection, these slight perturbations to cumulative summer precipitation are insignificant in the context of ensemble methodologies. Notably, the results suggest that groundwater representation in atmospheric modeling affects the response intensity of a land disturbance event. In the WRF-PF case, energy and atmospheric processes are more sensitive to disturbance in regions with higher water tables. Also, when dynamic subsurface hydrology is removed, WRF simulates a greater response to MPB at the land-atmosphere interface, including greater changes to daytime skin temperature, Bowen ratio and near-surface humidity. These findings highlight lower boundary representations in computational meteorology and numerical land-atmosphere modeling.

Smaller global and regional carbon emissions from gross land use change when considering sub-grid secondary land cohorts in a global dynamic vegetation model

NASA Astrophysics Data System (ADS)

Yue, Chao; Ciais, Philippe; Li, Wei

2018-02-01

Several modelling studies reported elevated carbon emissions from historical land use change (ELUC) by including bidirectional transitions on the sub-grid scale (termed gross land use change), dominated by shifting cultivation and other land turnover processes. However, most dynamic global vegetation models (DGVMs) that have implemented gross land use change either do not account for sub-grid secondary lands, or often have only one single secondary land tile over a model grid cell and thus cannot account for various rotation lengths in shifting cultivation and associated secondary forest age dynamics. Therefore, it remains uncertain how realistic the past ELUC estimations are and how estimated ELUC will differ between the two modelling approaches with and without multiple sub-grid secondary land cohorts - in particular secondary forest cohorts. Here we investigated historical ELUC over 1501-2005 by including sub-grid forest age dynamics in a DGVM. We run two simulations, one with no secondary forests (Sageless) and the other with sub-grid secondary forests of six age classes whose demography is driven by historical land use change (Sage). Estimated global ELUC for 1501-2005 is 176 Pg C in Sage compared to 197 Pg C in Sageless. The lower ELUC values in Sage arise mainly from shifting cultivation in the tropics under an assumed constant rotation length of 15 years, being 27 Pg C in Sage in contrast to 46 Pg C in Sageless. Estimated cumulative ELUC values from wood harvest in the Sage simulation (31 Pg C) are however slightly higher than Sageless (27 Pg C) when the model is forced by reconstructed harvested areas because secondary forests targeted in Sage for harvest priority are insufficient to meet the prescribed harvest area, leading to wood harvest being dominated by old primary forests. An alternative approach to quantify wood harvest ELUC, i.e. always harvesting the close-to-mature forests in both Sageless and Sage, yields similar values of 33 Pg C by both simulations. The lower ELUC from shifting cultivation in Sage simulations depends on the predefined forest clearing priority rules in the model and the assumed rotation length. A set of sensitivity model runs over Africa reveal that a longer rotation length over the historical period likely results in higher emissions. Our results highlight that although gross land use change as a former missing emission component is included by a growing number of DGVMs, its contribution to overall ELUC remains uncertain and tends to be overestimated when models ignore sub-grid secondary forests.

Surrogate Based Uni/Multi-Objective Optimization and Distribution Estimation Methods

NASA Astrophysics Data System (ADS)

Gong, W.; Duan, Q.; Huo, X.

2017-12-01

Parameter calibration has been demonstrated as an effective way to improve the performance of dynamic models, such as hydrological models, land surface models, weather and climate models etc. Traditional optimization algorithms usually cost a huge number of model evaluations, making dynamic model calibration very difficult, or even computationally prohibitive. With the help of a serious of recently developed adaptive surrogate-modelling based optimization methods: uni-objective optimization method ASMO, multi-objective optimization method MO-ASMO, and probability distribution estimation method ASMO-PODE, the number of model evaluations can be significantly reduced to several hundreds, making it possible to calibrate very expensive dynamic models, such as regional high resolution land surface models, weather forecast models such as WRF, and intermediate complexity earth system models such as LOVECLIM. This presentation provides a brief introduction to the common framework of adaptive surrogate-based optimization algorithms of ASMO, MO-ASMO and ASMO-PODE, a case study of Common Land Model (CoLM) calibration in Heihe river basin in Northwest China, and an outlook of the potential applications of the surrogate-based optimization methods.

Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)

DOE PAGES

Sakaguchi, K.; Zeng, X.; Leung, L. R.; ...

2016-12-21

Land carbon sensitivity to atmospheric CO 2 concentration (β L) and climate warming (γ L) is a crucial part of carbon-climate feedbacks in the earth system. Using the Community Land Model version 4 with a coupled carbon-nitrogen cycle, we examine whether the inclusion of a dynamic global vegetation model (CNDV) significantly changes the land carbon sensitivity from that obtained with prescribed vegetation cover (CN). For decadal timescale in the late twentieth century, β L is not substantially different between the two models but γ L of CNDV is stronger (more negative) than that of CN. The main reason for themore » difference in γL is not the concurrent change in vegetation cover driving the carbon dynamics, but rather the smaller nitrogen constraint on plant growth in CNDV compared with CN, which arises from the deviation of CNDV's near-equilibrium vegetation distribution from CN’s prescribed, historical land cover. The smaller nitrogen constraint makes the enhanced nitrogen mineralization with warming less effective in stimulating plant productivity to counter moisture stress in a warmer climate, leading to a more negative γ L. This represents a new indirect pathway that has not been identified for dynamic vegetation in the coupled carbon-nitrogen cycle to affect the terrestrial carbon-climate feedbacks in the earth system.« less

Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)

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

Sakaguchi, K.; Zeng, X.; Leung, L. R.

Land carbon sensitivity to atmospheric CO 2 concentration (β L) and climate warming (γ L) is a crucial part of carbon-climate feedbacks in the earth system. Using the Community Land Model version 4 with a coupled carbon-nitrogen cycle, we examine whether the inclusion of a dynamic global vegetation model (CNDV) significantly changes the land carbon sensitivity from that obtained with prescribed vegetation cover (CN). For decadal timescale in the late twentieth century, β L is not substantially different between the two models but γ L of CNDV is stronger (more negative) than that of CN. The main reason for themore » difference in γL is not the concurrent change in vegetation cover driving the carbon dynamics, but rather the smaller nitrogen constraint on plant growth in CNDV compared with CN, which arises from the deviation of CNDV's near-equilibrium vegetation distribution from CN’s prescribed, historical land cover. The smaller nitrogen constraint makes the enhanced nitrogen mineralization with warming less effective in stimulating plant productivity to counter moisture stress in a warmer climate, leading to a more negative γ L. This represents a new indirect pathway that has not been identified for dynamic vegetation in the coupled carbon-nitrogen cycle to affect the terrestrial carbon-climate feedbacks in the earth system.« less

Signature project 1B-integrated land-use, transportation and environmental modeling.

DOT National Transportation Integrated Search

2014-05-01

Land use and transportation are inextricably linked. Models that capture the dynamics and interactions of both systems are indispensable for evaluating alternative courses of action in policy and investment. These models must be spatially disaggregat...

Effects of anthropogenic land-subsidence on inundation dynamics: the case study of Ravenna, Italy

NASA Astrophysics Data System (ADS)

Carisi, Francesca; Domeneghetti, Alessio; Castellarin, Attilio

2016-05-01

Can differential land-subsidence significantly alter river flooding dynamics, and thus flood risk in flood prone areas? Many studies show how the lowering of the coastal areas is closely related to an increase in the flood-hazard due to more important tidal flooding and see level rise. The literature on the relationship between differential land-subsidence and possible alterations to riverine flood-hazard of inland areas is still sparse, although several geographical areas characterized by significant land-subsidence rates during the last 50 years experienced intensification in both inundation magnitude and frequency. We investigate the possible impact of a significant differential ground lowering on flood hazard over a 77 km2 area around the city of Ravenna, in Italy. The rate of land-subsidence in the study area, naturally in the order of a few mm year-1, dramatically increased up to 110 mm year-1 after World War II, primarily due to groundwater pumping and gas production platforms. The result was a cumulative drop that locally exceeds 1.5 m. Using a recent digital elevation model (res. 5 m) and literature data on land-subsidence, we constructed a ground elevation model over the study area in 1897 and we characterized either the current and the historical DEM with or without road embankments and land-reclamation channels in their current configuration. We then considered these four different topographic models and a two-dimensional hydrodynamic model to simulate and compare the inundation dynamics associated with a levee failure scenario along embankment system of the river Montone, which flows eastward in the southern portion of the study area. For each topographic model, we quantified the flood hazard in terms of maximum water depth (h) and we compared the actual effects on flood-hazard dynamics of differential land-subsidence relative to those associated with other man-made topographic alterations, which resulted to be much more significant.

Integrating macro and micro scale approaches in the agent-based modeling of residential dynamics

NASA Astrophysics Data System (ADS)

Saeedi, Sara

2018-06-01

With the advancement of computational modeling and simulation (M&S) methods as well as data collection technologies, urban dynamics modeling substantially improved over the last several decades. The complex urban dynamics processes are most effectively modeled not at the macro-scale, but following a bottom-up approach, by simulating the decisions of individual entities, or residents. Agent-based modeling (ABM) provides the key to a dynamic M&S framework that is able to integrate socioeconomic with environmental models, and to operate at both micro and macro geographical scales. In this study, a multi-agent system is proposed to simulate residential dynamics by considering spatiotemporal land use changes. In the proposed ABM, macro-scale land use change prediction is modeled by Artificial Neural Network (ANN) and deployed as the agent environment and micro-scale residential dynamics behaviors autonomously implemented by household agents. These two levels of simulation interacted and jointly promoted urbanization process in an urban area of Tehran city in Iran. The model simulates the behavior of individual households in finding ideal locations to dwell. The household agents are divided into three main groups based on their income rank and they are further classified into different categories based on a number of attributes. These attributes determine the households' preferences for finding new dwellings and change with time. The ABM environment is represented by a land-use map in which the properties of the land parcels change dynamically over the simulation time. The outputs of this model are a set of maps showing the pattern of different groups of households in the city. These patterns can be used by city planners to find optimum locations for building new residential units or adding new services to the city. The simulation results show that combining macro- and micro-level simulation can give full play to the potential of the ABM to understand the driving mechanism of urbanization and provide decision-making support for urban management.

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.

Model-data integration to improve the LPJmL dynamic global vegetation model

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Thonicke, Kirsten; Schaphoff, Sibyll; Thurner, Martin; von Bloh, Werner; Dorigo, Wouter; Carvalhais, Nuno

2017-04-01

Dynamic global vegetation models show large uncertainties regarding the development of the land carbon balance under future climate change conditions. This uncertainty is partly caused by differences in how vegetation carbon turnover is represented in global vegetation models. Model-data integration approaches might help to systematically assess and improve model performances and thus to potentially reduce the uncertainty in terrestrial vegetation responses under future climate change. Here we present several applications of model-data integration with the LPJmL (Lund-Potsdam-Jena managed Lands) dynamic global vegetation model to systematically improve the representation of processes or to estimate model parameters. In a first application, we used global satellite-derived datasets of FAPAR (fraction of absorbed photosynthetic activity), albedo and gross primary production to estimate phenology- and productivity-related model parameters using a genetic optimization algorithm. Thereby we identified major limitations of the phenology module and implemented an alternative empirical phenology model. The new phenology module and optimized model parameters resulted in a better performance of LPJmL in representing global spatial patterns of biomass, tree cover, and the temporal dynamic of atmospheric CO2. Therefore, we used in a second application additionally global datasets of biomass and land cover to estimate model parameters that control vegetation establishment and mortality. The results demonstrate the ability to improve simulations of vegetation dynamics but also highlight the need to improve the representation of mortality processes in dynamic global vegetation models. In a third application, we used multiple site-level observations of ecosystem carbon and water exchange, biomass and soil organic carbon to jointly estimate various model parameters that control ecosystem dynamics. This exercise demonstrates the strong role of individual data streams on the simulated ecosystem dynamics which consequently changed the development of ecosystem carbon stocks and fluxes under future climate and CO2 change. In summary, our results demonstrate challenges and the potential of using model-data integration approaches to improve a dynamic global vegetation model.

A method for landing gear modeling and simulation with experimental validation

NASA Technical Reports Server (NTRS)

Daniels, James N.

1996-01-01

This document presents an approach for modeling and simulating landing gear systems. Specifically, a nonlinear model of an A-6 Intruder Main Gear is developed, simulated, and validated against static and dynamic test data. This model includes nonlinear effects such as a polytropic gas model, velocity squared damping, a geometry governed model for the discharge coefficients, stick-slip friction effects and a nonlinear tire spring and damping model. An Adams-Moulton predictor corrector was used to integrate the equations of motion until a discontinuity caused by a stick-slip friction model was reached, at which point, a Runga-Kutta routine integrated past the discontinuity and returned the problem solution back to the predictor corrector. Run times of this software are around 2 mins. per 1 sec. of simulation under dynamic circumstances. To validate the model, engineers at the Aircraft Landing Dynamics facilities at NASA Langley Research Center installed one A-6 main gear on a drop carriage and used a hydraulic shaker table to provide simulated runway inputs to the gear. Model parameters were tuned to produce excellent agreement for many cases.

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

NASA Astrophysics Data System (ADS)

Tang, G.; Bartlein, P. J.

2012-01-01

Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p < 0.01) in the Everglades of Florida over the years 1996-2001. The modeled monthly soil moisture for Illinois of the US agrees well (R2 = 0.79, p < 0.01) with the observed over the years 1984-2001. The modeled monthly stream flow for most 12 major rivers in the US is consistent R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficients >0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

Comparing the Performance of Three Land Models in Global C Cycle Simulations: A Detailed Structural Analysis: Structural Analysis of Land Models

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

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra

Land models are valuable tools to understand the dynamics of global carbon (C) cycle. Various models have been developed and used for predictions of future C dynamics but uncertainties still exist. Diagnosing the models’ behaviors in terms of structures can help to narrow down the uncertainties in prediction of C dynamics. In this study three widely used land surface models, namely CSIRO’s Atmosphere Biosphere Land Exchange (CABLE) with 9 C pools, Community Land Model (version 3.5) combined with Carnegie-Ames-Stanford Approach (CLM-CASA) with 12 C pools and Community Land Model (version 4) (CLM4) with 26 C pools were driven by themore » observed meteorological forcing. The simulated C storage and residence time were used for analysis. The C storage and residence time were computed globally for all individual soil and plant pools, as well as net primary productivity (NPP) and its allocation to different plant components’ based on these models. Remotely sensed NPP and statistically derived HWSD, and GLC2000 datasets were used as a reference to evaluate the performance of these models. Results showed that CABLE exhibited better agreement with referenced C storage and residence time for plant and soil pools, as compared with CLM-CASA and CLM4. CABLE had longer bulk residence time for soil C pools and stored more C in roots, whereas, CLM-CASA and CLM4 stored more C in woody pools due to differential NPP allocation. Overall, these results indicate that the differences in C storage and residence times in three models are largely due to the differences in their fundamental structures (number of C pools), NPP allocation and C transfer rates. Our results have implications in model development and provide a general framework to explain the bias/uncertainties in simulation of C storage and residence times from the perspectives of model structures.« less

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

Treesearch

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

2011-01-01

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

Examining the Effects of Mosaic Land Cover on Extreme Events in Historical Downscaled WRF Simulations

EPA Science Inventory

The representation of land use and land cover (hereby referred to as “LU”) is a challenging aspect of dynamically downscaled simulations, as a mesoscale model that is utilized as a regional climate model (RCM) may be limited in its ability to represent LU over multi-d...

UVM Transportation Research Center signature project 1B : integrated land-use, transportation and environmental modeling.

DOT National Transportation Integrated Search

2014-05-01

Land use and transportation are inextricably linked. Models that capture the dynamics and interactions : of both systems are indispensable for evaluating alternative courses of action in policy and investment. : These models must be spatially disaggr...

Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media

PubMed Central

Watson, Keri B.; Wood, Spencer A.; Ricketts, Taylor H.

2016-01-01

Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18–20.2 at 95% confidence) to Vermont’s tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making. PMID:27611325

Acceleration Measurements During Landings of a 1/5.5-Size Dynamic Model of the Columbia XJL-1 Amphibian in Smooth Water and in Waves: Langley Tank Model 208M, TED No. NACA 2336

NASA Technical Reports Server (NTRS)

Clement, Eugene P.; Havens, Robert F.

1947-01-01

A 1/5.5-size powered dynamic model of the Columbia XJL-1 amphibian was landed in Langley tank no. 1 in smooth water and in oncoming waves of heights from 2.1 feet to 6.4 feet (full-size) and lengths from 50 feet to 264 feet (full-size). The motions and the vertical accelerations of the model were continuously recorded. The greatest vertical acceleration measured during the smooth-water landings was 3.1g. During landings in rough water the greatest vertical acceleration measured was 15.4g, for a landing in 6.4-foot by 165-foot waves. The impact accelerations increased with increase in wave height and, in general, decreased with increase in wave length. During the landings in waves the model bounced into the air at stalled attitudes at speeds below flying speed. The model trimmed up to the mechanical trim stop (20 deg) during landings in waves of heights greater than 2.0 feet. Solid water came over the bow and damaged the propeller during one landing in 6.4-foot waves. The vertical acceleration coefficients at first impact from the tank tests of a 1/5.5-size model were in fair agreement with data obtained at the Langley impact basin during tests of a 1/2-size model of the hull.

Space shuttle flying qualities and criteria assessment

NASA Technical Reports Server (NTRS)

Myers, T. T.; Johnston, D. E.; Mcruer, Duane T.

1987-01-01

Work accomplished under a series of study tasks for the Flying Qualities and Flight Control Systems Design Criteria Experiment (OFQ) of the Shuttle Orbiter Experiments Program (OEX) is summarized. The tasks involved review of applicability of existing flying quality and flight control system specification and criteria for the Shuttle; identification of potentially crucial flying quality deficiencies; dynamic modeling of the Shuttle Orbiter pilot/vehicle system in the terminal flight phases; devising a nonintrusive experimental program for extraction and identification of vehicle dynamics, pilot control strategy, and approach and landing performance metrics, and preparation of an OEX approach to produce a data archive and optimize use of the data to develop flying qualities for future space shuttle craft in general. Analytic modeling of the Orbiter's unconventional closed-loop dynamics in landing, modeling pilot control strategies, verification of vehicle dynamics and pilot control strategy from flight data, review of various existent or proposed aircraft flying quality parameters and criteria in comparison with the unique dynamic characteristics and control aspects of the Shuttle in landing; and finally a summary of conclusions and recommendations for developing flying quality criteria and design guides for future Shuttle craft.

Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes

NASA Astrophysics Data System (ADS)

Ekici, A.; Chadburn, S.; Chaudhary, N.; Hajdu, L. H.; Marmy, A.; Peng, S.; Boike, J.; Burke, E.; Friend, A. D.; Hauck, C.; Krinner, G.; Langer, M.; Miller, P. A.; Beer, C.

2015-07-01

Modeling soil thermal dynamics at high latitudes and altitudes requires representations of physical processes such as snow insulation, soil freezing and thawing and subsurface conditions like soil water/ice content and soil texture. We have compared six different land models: JSBACH, ORCHIDEE, JULES, COUP, HYBRID8 and LPJ-GUESS, at four different sites with distinct cold region landscape types, to identify the importance of physical processes in capturing observed temperature dynamics in soils. The sites include alpine, high Arctic, wet polygonal tundra and non-permafrost Arctic, thus showing how a range of models can represent distinct soil temperature regimes. For all sites, snow insulation is of major importance for estimating topsoil conditions. However, soil physics is essential for the subsoil temperature dynamics and thus the active layer thicknesses. This analysis shows that land models need more realistic surface processes, such as detailed snow dynamics and moss cover with changing thickness and wetness, along with better representations of subsoil thermal dynamics.

Effect of water table dynamics on land surface hydrologic memory

NASA Astrophysics Data System (ADS)

Lo, Min-Hui; Famiglietti, James S.

2010-11-01

The representation of groundwater dynamics in land surface models has received considerable attention in recent years. Most studies have found that soil moisture increases after adding a groundwater component because of the additional supply of water to the root zone. However, the effect of groundwater on land surface hydrologic memory (persistence) has not been explored thoroughly. In this study we investigate the effect of water table dynamics on National Center for Atmospheric Research Community Land Model hydrologic simulations in terms of land surface hydrologic memory. Unlike soil water or evapotranspiration, results show that land surface hydrologic memory does not always increase after adding a groundwater component. In regions where the water table level is intermediate, land surface hydrologic memory can even decrease, which occurs when soil moisture and capillary rise from groundwater are not in phase with each other. Further, we explore the hypothesis that in addition to atmospheric forcing, groundwater variations may also play an important role in affecting land surface hydrologic memory. Analyses show that feedbacks of groundwater on land surface hydrologic memory can be positive, negative, or neutral, depending on water table dynamics. In regions where the water table is shallow, the damping process of soil moisture variations by groundwater is not significant, and soil moisture variations are mostly controlled by random noise from atmospheric forcing. In contrast, in regions where the water table is very deep, capillary fluxes from groundwater are small, having limited potential to affect soil moisture variations. Therefore, a positive feedback of groundwater to land surface hydrologic memory is observed in a transition zone between deep and shallow water tables, where capillary fluxes act as a buffer by reducing high-frequency soil moisture variations resulting in longer land surface hydrologic memory.

Comparisons with observational and experimental manipulation data imply needed conceptual changes to ESM land models

NASA Astrophysics Data System (ADS)

Riley, W. J.; Zhu, Q.; Tang, J.

2016-12-01

The land models integrated in Earth System Models (ESMs) are critical components necessary to predict soil carbon dynamics and carbon-climate interactions under a changing climate. Yet, these models have been shown to have poor predictive power when compared with observations and ignore many processes known to the observational communities to influence above and belowground carbon dynamics. Here I will report work to tightly couple observations and perturbation experiment results with development of an ESM land model (ALM), focusing on nutrient constraints of the terrestrial C cycle. Using high-frequency flux tower observations and short-term nitrogen and phosphorus perturbation experiments, we show that conceptualizing plant and soil microbe interactions as a multi-substrate, multi-competitor kinetic network allows for accurate prediction of nutrient acquisition. Next, using multiple-year FACE and fertilization response observations at many forest sites, we show that capturing the observed responses requires representation of dynamic allocation to respond to the resulting stresses. Integrating the mechanisms implied by these observations into ALM leads to much lower observational bias and to very different predictions of long-term soil and aboveground C stocks and dynamics, and therefore C-climate feedbacks. I describe how these types of observational constraints are being integrated into the open-source International Land Model Benchmarking (ILAMB) package, and end with the argument that consolidating as many observations of all sorts for easy use by modelers is an important goal to improve C-climate feedback predictions.

A review and assessment of land-use change models: dynamics of space, time, and human choice

Treesearch

Chetan Agarwal; Glen M. Green; J. Morgan Grove; Tom P. Evans; Charles M. Schweik

2002-01-01

A review of different types of land-use change models incorporating human processes. Presents a framework to compare land-use change models in terms of scale (both spatial and temporal) and complexity, and how well they incorporate space, time, and human decisionmaking. Examines a summary set of 250 relevant citations and develops a bibliography of 136 papers. From...

Phase 1 report : UVM transportation research center signature project 1B : integrated land use, transportation and environmental modeling.

DOT National Transportation Integrated Search

2010-07-01

Land use and transportation are inextricably linked. Models that capture the dynamics and interactions of both systems are indispensable for evaluating alternative courses of action in policy and investment. These models must be spatially disaggregat...

Combining surface reanalysis and remote sensing data for monitoring evapotranspiration

USGS Publications Warehouse

Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, Pat; Williams, C.; Ardö, J.; Marie, B.; Cappelaere, B.; Grandcourt, A.; Nickless, A.; Noubellon, Y.; Scholes, R.; Kutsch, W.

2012-01-01

Climate change is expected to have the greatest impact on the world's poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.

Dynamic reserve selection: Optimal land retention with land-price feedbacks

Treesearch

Sandor F. Toth; Robert G. Haight; Luke W. Rogers

2011-01-01

Urban growth compromises open space and ecosystem functions. To mitigate the negative effects, some agencies use reserve selection models to identify conservation sites for purchase or retention. Existing models assume that conservation has no impact on nearby land prices. We propose a new integer program that relaxes this assumption via adaptive cost coefficients. Our...

A Dynamic Simulation Model of Land-Use, Population, and Rural Livelihoods in the Central Rift Valley of Ethiopia

NASA Astrophysics Data System (ADS)

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households' income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process.

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.

Dynamic Model Investigation of Water Pressures and Accelerations Encountered During Landings of the Apollo Spacecraft

NASA Technical Reports Server (NTRS)

Stubbs, Sandy M.

1967-01-01

An experimental investigation was made to determine impact water pressures, accelerations, and landing dynamics of a 1/4-scale dynamic model of the command module of the Apollo spacecraft. A scaled-stiffness aft heat shield was used on the model to simulate the structural deflections of the full-scale heat shield. Tests were made on water to obtain impact pressure data at a simulated parachute letdown (vertical) velocity component of approximately 30 ft/sec (9.1 m/sec) full scale. Additional tests were made on water, sand, and hard clay-gravel landing surfaces at simulated vertical velocity components of 23 ft/sec (7.0 m/sec) full scale. Horizontal velocity components investigated ranged from 0 to 50 ft/sec (15 m/sec) full scale and the pitch attitudes ranged from -40 degrees to 29 degrees. Roll attitudes were O degrees, 90 degrees, and 180 degrees, and the yaw attitude was 0 degrees.

Examining lag effects between industrial land development and regional economic changes: The Netherlands experience.

PubMed

Ustaoglu, Eda; Lavalle, Carlo

2017-01-01

In most empirical applications, forecasting models for the analysis of industrial land focus on the relationship between current values of economic parameters and industrial land use. This paper aims to test this assumption by focusing on the dynamic relationship between current and lagged values of the 'economic fundamentals' and industrial land development. Not much effort has yet been attributed to develop land forecasting models to predict the demand for industrial land except those applying static regressions or other statistical measures. In this research, we estimated a dynamic panel data model across 40 regions from 2000 to 2008 for the Netherlands to uncover the relationship between current and lagged values of economic parameters and industrial land development. Land-use regulations such as land zoning policies, and other land-use restrictions like natural protection areas, geographical limitations in the form of water bodies or sludge areas are expected to affect supply of land, which will in turn be reflected in industrial land market outcomes. Our results suggest that gross domestic product (GDP), industrial employment, gross value added (GVA), property price, and other parameters representing demand and supply conditions in the industrial market explain industrial land developments with high significance levels. It is also shown that contrary to the current values, lagged values of the economic parameters have more sound relationships with the industrial developments in the Netherlands. The findings suggest use of lags between selected economic parameters and industrial land use in land forecasting applications.

Examining lag effects between industrial land development and regional economic changes: The Netherlands experience

PubMed Central

Ustaoglu, Eda; Lavalle, Carlo

2017-01-01

In most empirical applications, forecasting models for the analysis of industrial land focus on the relationship between current values of economic parameters and industrial land use. This paper aims to test this assumption by focusing on the dynamic relationship between current and lagged values of the ‘economic fundamentals’ and industrial land development. Not much effort has yet been attributed to develop land forecasting models to predict the demand for industrial land except those applying static regressions or other statistical measures. In this research, we estimated a dynamic panel data model across 40 regions from 2000 to 2008 for the Netherlands to uncover the relationship between current and lagged values of economic parameters and industrial land development. Land-use regulations such as land zoning policies, and other land-use restrictions like natural protection areas, geographical limitations in the form of water bodies or sludge areas are expected to affect supply of land, which will in turn be reflected in industrial land market outcomes. Our results suggest that gross domestic product (GDP), industrial employment, gross value added (GVA), property price, and other parameters representing demand and supply conditions in the industrial market explain industrial land developments with high significance levels. It is also shown that contrary to the current values, lagged values of the economic parameters have more sound relationships with the industrial developments in the Netherlands. The findings suggest use of lags between selected economic parameters and industrial land use in land forecasting applications. PMID:28877204

Study on a Dynamic Vegetation Model for Simulating Land Surface Flux Exchanges at Lien-Hua-Chih Flux Observation Site in Taiwan

NASA Astrophysics Data System (ADS)

Yeh, T. Y.; Li, M. H.; Chen, Y. Y.; Ryder, J.; McGrath, M.; Otto, J.; Naudts, K.; Luyssaert, S.; MacBean, N.; Bastrikov, V.

2016-12-01

Dynamic vegetation model ORCHIDEE (Organizing Carbon and Hydrology In Dynamic EcosystEms) is a state of art land surface component of the IPSL (Institute Pierre Simon Laplace) Earth System Model. It has been used world-wide to investigate variations of water, carbon, and energy exchanges between the land surface and the atmosphere. In this study we assessed the applicability of using ORCHIDEE-CAN, a new feature with 3-D CANopy structure (Naudts et al., 2015; Ryder et al., 2016), to simulate surface fluxes measured at tower-based eddy covariance fluxes at the Lien-Hua-Chih experimental watershed in Taiwan. The atmospheric forcing including radiation, air temperature, wind speed, and the dynamics of vertical canopy structure for driving the model were obtained from the observations site. Suitable combinations of default plant function types were examined to meet in-situ observations of soil moisture and leaf area index from 2009 to 2013. The simulated top layer soil moisture was ranging from 0.1 to 0.4 and total leaf area was ranging from 2.2 to 4.4, respectively. A sensitivity analysis was performed to investigate the sensitive of model parameters and model skills of ORCHIDEE-CAN on capturing seasonal variations of surface fluxes. The most sensitive parameters were suggested and calibrated by an automatic data assimilation tool ORCHDAS (ORCHIDEE Data Assimilation Systems; http://orchidas.lsce.ipsl.fr/). Latent heat, sensible heat, and carbon fluxes simulated by the model were compared with long-term observations at the site. ORCHIDEE-CAN by making use of calibrated surface parameters was used to study variations of land-atmosphere interactions on a variety of temporal scale in associations with changes in both land and atmospheric conditions. Ref: Naudts, K., et al.,: A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes, Geoscientific Model Development, 8, 2035-2065, doi:10.5194/gmd-8-2035-2015,2015. Ryder, J., et al. : A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations, Geoscientific Model Development, 9, 223-245, doi:10.5194/gmd-9-223-2016, 2016.

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.

Carbon dynamics and land-use choices: building a regional-scale multidisciplinary model

USGS Publications Warehouse

Kerr, Suzi; Liu, Shu-Guang; Pfaff, Alexander S.P.; Hughes, R. Flint

2003-01-01

Policy enabling tropical forests to approach their potential contribution to global-climate-change mitigation requires forecasts of land use and carbon storage on a large scale over long periods. In this paper, we present an integrated modeling methodology that addresses these needs. We model the dynamics of the human land-use system and of C pools contained in each ecosystem, as well as their interactions. The model is national scale, and is currently applied in a preliminary way to Costa Rica using data spanning a period of over 50 years. It combines an ecological process model, parameterized using field and other data, with an economic model, estimated using historical data to ensure a close link to actual behavior. These two models are linked so that ecological conditions affect land-use choices and vice versa. The integrated model predicts land use and its consequences for C storage for policy scenarios. These predictions can be used to create baselines, reward sequestration, and estimate the value in both environmental and economic terms of including C sequestration in tropical forests as part of the efforts to mitigate global climate change. The model can also be used to assess the benefits from costly activities to increase accuracy and thus reduce errors and their societal costs.

Modeling the spatially dynamic distribution of humans in the Oregon (USA) coast range.

Treesearch

Jeffrey D. Kline; David L. Azuma; Alissa Moses

2003-01-01

A common approach to land use change analyses in multidisciplinary landscape-level studies is to delineate discrete forest and non-forest or urban and non-urban land use categories to serve as inputs into sets of integrated sub-models describing socioeconomic and ecological processes. Such discrete land use categories, however, may be inappropriate when the...

Incorporating human-water dynamics in a hyper-resolution land surface model

NASA Astrophysics Data System (ADS)

Vergopolan, N.; Chaney, N.; Wanders, N.; Sheffield, J.; Wood, E. F.

2017-12-01

The increasing demand for water, energy, and food is leading to unsustainable groundwater and surface water exploitation. As a result, the human interactions with the environment, through alteration of land and water resources dynamics, need to be reflected in hydrologic and land surface models (LSMs). Advancements in representing human-water dynamics still leave challenges related to the lack of water use data, water allocation algorithms, and modeling scales. This leads to an over-simplistic representation of human water use in large-scale models; this is in turn leads to an inability to capture extreme events signatures and to provide reliable information at stakeholder-level spatial scales. The emergence of hyper-resolution models allows one to address these challenges by simulating the hydrological processes and interactions with the human impacts at field scales. We integrated human-water dynamics into HydroBlocks - a hyper-resolution, field-scale resolving LSM. HydroBlocks explicitly solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs); and its HRU-based model parallelization allows computationally efficient long-term simulations as well as ensemble predictions. The implemented human-water dynamics include groundwater and surface water abstraction to meet agricultural, domestic and industrial water demands. Furthermore, a supply-demand water allocation scheme based on relative costs helps to determine sectoral water use requirements and tradeoffs. A set of HydroBlocks simulations over the Midwest United States (daily, at 30-m spatial resolution for 30 years) are used to quantify the irrigation impacts on water availability. The model captures large reductions in total soil moisture and water table levels, as well as spatiotemporal changes in evapotranspiration and runoff peaks, with their intensity related to the adopted water management strategy. By incorporating human-water dynamics in a hyper-resolution LSM this work allows for progress on hydrological monitoring and predictions, as well as drought preparedness and water impact assessments at relevant decision-making scales.

Simulating Descent and Landing of a Spacecraft

NASA Technical Reports Server (NTRS)

Balaram, J.; Jain, Abhinandan; Martin, Bryan; Lim, Christopher; Henriquez, David; McMahon, Elihu; Sohl, Garrett; Banerjee, Pranab; Steele, Robert; Bentley, Timothy

2005-01-01

The Dynamics Simulator for Entry, Descent, and Surface landing (DSENDS) software performs high-fidelity simulation of the Entry, Descent, and Landing (EDL) of a spacecraft into the atmosphere and onto the surface of a planet or a smaller body. DSENDS is an extension of the DShell and DARTS programs, which afford capabilities for mathematical modeling of the dynamics of a spacecraft as a whole and of its instruments, actuators, and other subsystems. DSENDS enables the modeling (including real-time simulation) of flight-train elements and all spacecraft responses during various phases of EDL. DSENDS provides high-fidelity models of the aerodynamics of entry bodies and parachutes plus supporting models of atmospheres. Terrain and real-time responses of terrain-imaging radar and lidar instruments can also be modeled. The program includes modules for simulation of guidance, navigation, hypersonic steering, and powered descent. Automated state-machine-driven model switching is used to represent spacecraft separations and reconfigurations. Models for computing landing contact and impact forces are expected to be added. DSENDS can be used as a stand-alone program or incorporated into a larger program that simulates operations in real time.

Modeling habitat dynamics accounting for possible misclassification

USGS Publications Warehouse

Veran, Sophie; Kleiner, Kevin J.; Choquet, Remi; Collazo, Jaime; Nichols, James D.

2012-01-01

Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.

PROCEEDINGS OF THE CROSS DISCIPLINE ECOSYTEM MODELING AND ANALYSIS WORKSHOP

EPA Science Inventory

The complexity of environmental problems we face now and in the future is ever increasing. Process linkages among air, land, surface and subsurface water require interdisciplinary modeling approaches. The dynamics of land use change spurred by population and economic growth, ...

Forest cover change prediction using hybrid methodology of geoinformatics and Markov chain model: A case study on sub-Himalayan town Gangtok, India

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Anirban; Mondal, Arun; Mukherjee, Sandip; Khatua, Dipam; Ghosh, Subhajit; Mitra, Debasish; Ghosh, Tuhin

2014-08-01

In the Himalayan states of India, with increasing population and activities, large areas of forested land are being converted into other land-use features. There is a definite cause and effect relationship between changing practice for development and changes in land use. So, an estimation of land use dynamics and a futuristic trend pattern is essential. A combination of geospatial and statistical techniques were applied to assess the present and future land use/land cover scenario of Gangtok, the subHimalayan capital of Sikkim. Multi-temporal satellite imageries of the Landsat series were used to map the changes in land use of Gangtok from 1990 to 2010. Only three major land use classes (built-up area and bare land, step cultivated area, and forest) were considered as the most dynamic land use practices of Gangtok. The conventional supervised classification, and spectral indices-based thresholding using NDVI (Normalized Difference Vegetation Index) and SAVI (Soil Adjusted Vegetation Index) were applied along with the accuracy assessments. Markov modelling was applied for prediction of land use/land cover change and was validated. SAVI provides the most accurate estimate, i.e., the difference between predicted and actual data is minimal. Finally, a combination of Markov modelling and SAVI was used to predict the probable land-use scenario in Gangtok in 2020 AD, which indicted that more forest areas will be converted for step cultivation by the year 2020.

Impact of dynamic vegetation phenology on the simulated pan-Arctic land surface state

NASA Astrophysics Data System (ADS)

Teufel, Bernardo; Sushama, Laxmi; Arora, Vivek K.; Verseghy, Diana

2018-03-01

The pan-Arctic land surface is undergoing rapid changes in a warming climate, with near-surface permafrost projected to degrade significantly during the twenty-first century. Vegetation-related feedbacks have the potential to influence the rate of degradation of permafrost. In this study, the impact of dynamic phenology on the pan-Arctic land surface state, particularly near-surface permafrost, for the 1961-2100 period, is assessed by comparing two simulations of the Canadian Land Surface Scheme (CLASS)—one with dynamic phenology, modelled using the Canadian Terrestrial Ecosystem Model (CTEM), and the other with prescribed phenology. These simulations are forced by atmospheric data from a transient climate change simulation of the 5th generation Canadian Regional Climate Model (CRCM5) for the Representative Concentration Pathway 8.5 (RCP8.5). Comparison of the CLASS coupled to CTEM simulation to available observational estimates of plant area index, spatial distribution of permafrost and active layer thickness suggests that the model captures reasonably well the overall distribution of vegetation and permafrost. It is shown that the most important impact of dynamic phenology on the land surface occurs through albedo and it is demonstrated for the first time that vegetation control on albedo during late spring and early summer has the highest potential to impact the degradation of permafrost. While both simulations show extensive near-surface permafrost degradation by the end of the twenty-first century, the strong projected response of vegetation to climate warming and increasing CO2 concentrations in the coupled simulation results in accelerated permafrost degradation in the northernmost continuous permafrost regions.

Photogrammetric Measurements of CEV Airbag Landing Attenuation Systems

NASA Technical Reports Server (NTRS)

Barrows, Danny A.; Burner, Alpheus W.; Berry, Felecia C.; Dismond, Harriett R.; Cate, Kenneth H.

2008-01-01

High-speed photogrammetric measurements are being used to assess the impact dynamics of the Orion Crew Exploration Vehicle (CEV) for ground landing contingency upon return to earth. Test articles representative of the Orion capsule are dropped at the NASA Langley Landing and Impact Research (LandIR) Facility onto a sand/clay mixture representative of a dry lakebed from elevations as high as 62 feet (18.9 meters). Two different types of test articles have been evaluated: (1) half-scale metal shell models utilized to establish baseline impact dynamics and soil characterization, and (2) geometric full-scale drop models with shock-absorbing airbags which are being evaluated for their ability to cushion the impact of the Orion CEV with the earth s surface. This paper describes the application of the photogrammetric measurement technique and provides drop model trajectory and impact data that indicate the performance of the photogrammetric measurement system.

The influence of subsurface hydrodynamics on convective precipitation

NASA Astrophysics Data System (ADS)

Rahman, A. S. M. M.; Sulis, M.; Kollet, S. J.

2014-12-01

The terrestrial hydrological cycle comprises complex processes in the subsurface, land surface, and atmosphere, which are connected via complex non-linear feedback mechanisms. The influence of subsurface hydrodynamics on land surface mass and energy fluxes has been the subject of previous studies. Several studies have also investigated the soil moisture-precipitation feedback, neglecting however the connection with groundwater dynamics. The objective of this study is to examine the impact of subsurface hydrodynamics on convective precipitation events via shallow soil moisture and land surface processes. A scale-consistent Terrestrial System Modeling Platform (TerrSysMP) that consists of an atmospheric model (COSMO), a land surface model (CLM), and a three-dimensional variably saturated groundwater-surface water flow model (ParFlow), is used to simulate hourly mass and energy fluxes over days with convective rainfall events over the Rur catchment, Germany. In order to isolate the effect of groundwater dynamics on convective precipitation, two different model configurations with identical initial conditions are considered. The first configuration allows the groundwater table to evolve through time, while a spatially distributed, temporally constant groundwater table is prescribed as a lower boundary condition in the second configuration. The simulation results suggest that groundwater dynamics influence land surface soil moisture, which in turn affects the atmospheric boundary layer (ABL) height by modifying atmospheric thermals. It is demonstrated that because of this sensitivity of ABL height to soil moisture-temperature feedback, the onset and magnitude of convective precipitation is influenced by subsurface hydrodynamics. Thus, the results provide insight into the soil moisture-precipitation feedback including groundwater dynamics in a physically consistent manner by closing the water cycle from aquifers to the atmosphere.

Evaluating the Community Land Model (CLM4.5) at a coniferous forest site in northwestern United States using flux and carbon-isotope measurements

Treesearch

Henrique F. Duarte; Brett M. Raczka; Daniel M. Ricciuto; John C. Lin; Charles D. Koven; Peter E. Thornton; David R. Bowling; Chun-Ta Lai; Kenneth J. Bible; James R. Ehleringer

2017-01-01

Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest...

Spatial landuse planning using land evaluation and dynamic system to define sustainable area of paddy field: Case study in Karawang Regency, West Java, Indonesia

NASA Astrophysics Data System (ADS)

Widiatmaka, Widiatmaka; Ambarwulan, Wiwin; Firmansyah, Irman; Munibah, Khursatul; Santoso, Paulus B. K.

2015-04-01

Indonesia is the country with the 4th largest population in the worlds; the population reached more than 237 million people. With rice as the staple food for more than 95 percent of the population, there is an important role of paddy field in Indonesian food security. Actually, paddy field in Java has produced 52,6% of the total rice production in Indonesia, showing the very high dependence of Indonesia on food production from paddy fields in Java island. Karawang Regency is one of the regions in West Java Province that contribute to the national food supply, due to its high soil fertility and its high extent of paddy field. Dynamics of land use change in this region are high because of its proximity to urban area; this dynamics has led to paddy field conversion to industry and residential landuse, which in turn change the regional rice production capacity. Decreasing paddy field landuse in this region could be serve as an example case of the general phenomena which occurred in Javanese rice production region. The objective of this study were: (i) to identify the suitable area for paddy field, (ii) to modelize the decreasing of paddy field in socio-economic context of the region, and (iii) to plan the spatial priority area of paddy field protection according to model prediction. A land evaluation for paddy was completed after a soil survey, while IKONOS imagery was analyzed to delineate paddy fields. Dynamic system model of paddy field land use is built, and then based on the model built, the land area of paddy field untill 2040 in some scenarios was developped. The research results showed that the land suitability class for paddy fields in Karawang Regency ranged from very suitable (S1) to marginally suitable (S3), with various land characteristics as limiting factors. The model predicts that if the situation of paddy field land use change continues in its business as usual path, paddy field area that would exist in the region in 2040 will stay half of the recent area. Based on the model, the scenario were developed for the protection of priority area. With such scenario, paddy field remains close to the value predicted oficially. Spatial information then can play a role by presenting the scenario spatially. Combining spatial information with land suitability, priority areas of paddy field protection can be delineated. Policies that followed also then be compiled, including the location of protection. Key-words: Land evaluation, food security, spatial information

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,...

Quantifying and Modelling Long Term Sediment Dynamics in Catchments in Western Europe

NASA Astrophysics Data System (ADS)

Notebaert, B.; De Brue, H.; Verstraeten, G.; Broothaerts, N.

2015-12-01

Quantification of sediment dynamics allows to get insight in driving forces and internal dynamics of the sediment cascade system. A useful tool to achieve this is the sediment budget approach, which encompasses the quantification of different sinks and sources. A Holocene time-differentiated sediment budget has been constructed for the Belgian Dijle River catchment (720 km²), based on a large set of field data. The results show how soil erosion is driven by land use changes over longer timescales. Sediment redistribution and the relative importance of the different sinks also vary over time, mainly as a result of changing land use and related landscape connectivity. However, the coarse temporal resolution typically associated with Holocene studies complicates the understanding of sub-millennial scale processes. In a second step, the field-based sediment budget was combined with a modeling approach using Watem/Sedem, a spatially distributed model that simulates soil erosion and colluvial deposition. After validation of the model calibration against the sediment budget, the model was used in a sensitivity analysis. Results confirm the overwhelming influence of human land use on both soil erosion and landscape connectivity, whereas the climatic impact is comparatively small. In addition to catchment-wide simulations, the model also served to test the relative importance of lynchets and dry valleys in different environments. Finally, the geomorphic model was used to simulate past land use, taking into account equifinality. For this purpose, a large series of hypothetical time-independent land use maps of the Dijle catchment were modeled based on a multi-objective allocation algorithm, and applied in Watem/Sedem. Modeled soil erosion and sediment deposition outcomes for each scenario were subsequently compared with the field-based record, taking into account uncertainties. As such, the model allows to evaluate and select realistic land use scenarios for the Holocene.

Studying urban land-atmospheric interactions by coupling an urban canopy model with a single column atmospheric models

NASA Astrophysics Data System (ADS)

Song, J.; Wang, Z.

2013-12-01

Studying urban land-atmospheric interactions by coupling an urban canopy model with a single column atmospheric models Jiyun Song and Zhi-Hua Wang School of Sustainable Engineering and the Built Environment, Arizona State University, PO Box 875306, Tempe, AZ 85287-5306 Landuse landcover changes in urban area will modify surface energy budgets, turbulent fluxes as well as dynamic and thermodynamic structures of the overlying atmospheric boundary layer (ABL). In order to study urban land-atmospheric interactions, we coupled a single column atmospheric model (SCM) to a cutting-edge single layer urban canopy model (SLUCM). Modification of surface parameters such as the fraction of vegetation and engineered pavements, thermal properties of building and pavement materials, and geometrical features of street canyon, etc. in SLUCM dictates the evolution of surface balance of energy, water and momentum. The land surface states then provide lower boundary conditions to the overlying atmosphere, which in turn modulates the modification of ABL structure as well as vertical profiles of temperature, humidity, wind speed and tracer gases. The coupled SLUCM-SCM model is tested against field measurements of surface layer fluxes as well as profiles of temperature and humidity in the mixed layer under convective conditions. After model test, SLUCM-SCM is used to simulate the effect of changing urban land surface conditions on the evolution of ABL structure and dynamics. Simulation results show that despite the prescribed atmospheric forcing, land surface states impose significant impact on the physics of the overlying vertical atmospheric layer. Overall, this numerical framework provides a useful standalone modeling tool to assess the impacts of urban land surface conditions on the local hydrometeorology through land-atmospheric interactions. It also has potentially far-reaching implications to urban ecohydrological services for cities under future expansion and climate challenges.

Using dry spell dynamics of land surface temperature to evaluate large-scale model representation of soil moisture control on evapotranspiration

NASA Astrophysics Data System (ADS)

Taylor, Christopher M.; Harris, Philip P.; Gallego-Elvira, Belen; Folwell, Sonja S.

2017-04-01

The soil moisture control on the partition of land surface fluxes between sensible and latent heat is a key aspect of land surface models used within numerical weather prediction and climate models. As soils dry out, evapotranspiration (ET) decreases, and the excess energy is used to warm the atmosphere. Poor simulations of this dynamic process can affect predictions of mean, and in particular, extreme air temperatures, and can introduce substantial biases into projections of climate change at regional scales. The lack of reliable observations of fluxes and root zone soil moisture at spatial scales that atmospheric models use (typically from 1 to several hundred kilometres), coupled with spatial variability in vegetation and soil properties, makes it difficult to evaluate the flux partitioning at the model grid box scale. To overcome this problem, we have developed techniques to use Land Surface Temperature (LST) to evaluate models. As soils dry out, LST rises, so it can be used under certain circumstances as a proxy for the partition between sensible and latent heat. Moreover, long time series of reliable LST observations under clear skies are available globally at resolutions of the order of 1km. Models can exhibit large biases in seasonal mean LST for various reasons, including poor description of aerodynamic coupling, uncertainties in vegetation mapping, and errors in down-welling radiation. Rather than compare long-term average LST values with models, we focus on the dynamics of LST during dry spells, when negligible rain falls, and the soil moisture store is drying out. The rate of warming of the land surface, or, more precisely, its warming rate relative to the atmosphere, emphasises the impact of changes in soil moisture control on the surface energy balance. Here we show the application of this approach to model evaluation, with examples at continental and global scales. We can compare the behaviour of both fully-coupled land-atmosphere models, and land surface models forced by observed meteorology. This approach provides insight into a fundamental process that affects predictions on multiple time scales, and which has an important impact for society.

Urban Dynamics: Analyzing Land Use Change in Urban Environments

NASA Technical Reports Server (NTRS)

Acevedo, William; Richards, Lora R.; Buchanan, Janis T.; Wegener, Whitney R.

2000-01-01

In FY99, the Earth Resource Observation System (EROS) staff at Ames continued managing the U.S. Geological Survey's (USGS) Urban Dynamics Research program, which has mapping and analysis activities at five USGS mapping centers. Historic land use reconstruction work continued while activities in geographic analysis and modeling were expanded. Retrospective geographic information system (GIS) development - the spatial reconstruction of a region's urban land-use history - focused on the Detroit River Corridor, California's Central Valley, and the city of Sioux Falls, South Dakota.

Impacts of climate and land-use changes on the hydrological dynamics in the upper Citarum River basin based on the J2000 hydrological model

NASA Astrophysics Data System (ADS)

Magenika Julian, Miga; Fink, Manfred; Fischer, Christian; Krause, Peter; Flügel, Wolfgang-Albert

2015-04-01

Changes of land-use and climate will most likely result in changes of the hydrological dynamics in river basins. Such changes can be noticed in the upper Citarum River basin (UCB), Java Island, Indonesia. This basin covers 1821km2 and is located in a hilly area of the backcountry of Jakarta. Between 2005 and 2009, the basin's forest cover has been reduced by 5.0%, residential areas grew around 8.2% expanding around the existing residential areas, and 3.9% of shrubland was converted into agricultural areas. From 1985 through 2009, the mean annual air temperature increased by 0.01° C/year; whereas, precipitation slightly decreased by 6.8mm/year. The process-oriented hydrological model JAMS/J2000 was adapted and implemented to assess the impact of land-use change and climate variability on the hydrological dynamics of this basin, including consideration of the temporal and spatial distributions. For this assessment, three scenarios based on realistic events were investigated; these consisted of the following (i) land-use changes in 2005 versus 2009; (ii) temperature increase from 1984 to 2009, while keeping a precipitation constant from year 1984; and (iii) variability of precipitation from 1984 to 2009, while keeping temperature constant from year 1984. The model-input conditions of land-use, precipitation, and temperature changes where applied individually, holding the other factors constant. Model simulations were conducted for the UCB. The J2000 model for the UCB was calibrated and validated using a split-sample approach. For model calibration and validation, fairly good objective functions were achieved: i.e. Nash-Sutcliffe efficiencies (E) by 0.79 and 0.76, log E of 0.89 and 0.84, coefficient of determination of 0.79 and 0.77, and a percent bias of -1.4% and -1.1%. From the model-simulation results, it was concluded that the land-use changes resulted in a slight increase in stream discharge (4.6%) and a decrease of evaporation of 3.7%. The analysis of the different runoff components indicated that, in particular, the amount of overland flow was estimated to increase 7.9%, primarily because of the significant expansion of residential areas. The individual effects of precipitation and temperature changes on the hydrological dynamics was evaluated for four five-year periods (1989-1993, 1994-1998, 1999-2003, and 2004-2009) for comparison with conditions for the first five-year period (1984-1988). The effect of a temperature increase from 1989 to 2009 on stream discharge was small, resulting in a reduction of about 1%. The increase of precipitation from 1985 to 1999 was affecting stream discharge by a small increase (2%). Through this application of the J2000, which proved to be an appropriate tool to assess environmental (land-use and climate) changes on the basin's hydrological dynamics, we could show that in the Indonesian test basin the observed change in land-use change might have a greater impact on hydrological dynamics than the impact of climate change. For future study, it is recommended to assess hydrological changes under the projected future climate and land-use conditions. Coupling effects of climate and land-use changes should be considered and assessed individually when quantifying the resultant hydrological changes estimated by the model.

Influence of crop type specification and spatial resolution on empirical modeling of field-scale Maize and Soybean carbon fluxes in the US Great Plains

NASA Astrophysics Data System (ADS)

McCombs, A. G.; Hiscox, A.; Wang, C.; Desai, A. R.

2016-12-01

A challenge in satellite land surface remote-sensing models of ecosystem carbon dynamics in agricultural systems is the lack of differentiation by crop type and management. This generalization can lead to large discrepancies between model predictions and eddy covariance flux tower observations of net ecosystem exchange of CO2 (NEE). Literature confirms that NEE varies remarkably among different crop types making the generalization of agriculture in remote sensing based models inaccurate. Here, we address this inaccuracy by identifying and mapping net ecosystem exchange (NEE) in agricultural fields by comparing bulk modeling and modeling by crop type, and using this information to develop empirical models for future use. We focus on mapping NEE in maize and soybean fields in the US Great Plains at higher spatial resolution using the fusion of MODIS and LandSAT surface reflectance. MODIS observed reflectance was downscaled using the ESTARFM downscaling methodology to match spatial scales to those found in LandSAT and that are more appropriate for carbon dynamics in agriculture fields. A multiple regression model was developed from surface reflectance of the downscaled MODIS and LandSAT remote sensing values calibrated against five FLUXNET/AMERIFLUX flux towers located on soybean and/or maize agricultural fields in the US Great Plains with multi-year NEE observations. Our new methodology improves upon bulk approximates to map and model carbon dynamics in maize and soybean fields, which have significantly different photosynthetic capacities.

Bridging the Gap Between the iLEAPS and GEWEX Land-Surface Modeling Communities

NASA Technical Reports Server (NTRS)

Bonan, Gordon; Santanello, Joseph A., Jr.

2013-01-01

Models of Earth's weather and climate require fluxes of momentum, energy, and moisture across the land-atmosphere interface to solve the equations of atmospheric physics and dynamics. Just as atmospheric models can, and do, differ between weather and climate applications, mostly related to issues of scale, resolved or parameterised physics,and computational requirements, so too can the land models that provide the required surface fluxes differ between weather and climate models. Here, however, the issue is less one of scale-dependent parameterisations.Computational demands can influence other minor land model differences, especially with respect to initialisation, data assimilation, and forecast skill. However, the distinction among land models (and their development and application) is largely driven by the different science and research needs of the weather and climate communities.

A dynamic simulation model of land-use, population, and rural livelihoods in the Central Rift Valley of Ethiopia.

PubMed

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households' income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process.

The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations

NASA Astrophysics Data System (ADS)

Walters, David; Boutle, Ian; Brooks, Malcolm; Melvin, Thomas; Stratton, Rachel; Vosper, Simon; Wells, Helen; Williams, Keith; Wood, Nigel; Allen, Thomas; Bushell, Andrew; Copsey, Dan; Earnshaw, Paul; Edwards, John; Gross, Markus; Hardiman, Steven; Harris, Chris; Heming, Julian; Klingaman, Nicholas; Levine, Richard; Manners, James; Martin, Gill; Milton, Sean; Mittermaier, Marion; Morcrette, Cyril; Riddick, Thomas; Roberts, Malcolm; Sanchez, Claudio; Selwood, Paul; Stirling, Alison; Smith, Chris; Suri, Dan; Tennant, Warren; Vidale, Pier Luigi; Wilkinson, Jonathan; Willett, Martin; Woolnough, Steve; Xavier, Prince

2017-04-01

We describe Global Atmosphere 6.0 and Global Land 6.0 (GA6.0/GL6.0): the latest science configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame (Even Newer Dynamics for General atmospheric modelling of the environment) dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model's physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe GA6.1/GL6.1, which includes a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global numerical weather prediction, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

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

Jiao, Yang; Lei, Huimin; Yang, Dawen

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

46 CFR 162.060-26 - Land-based testing requirements.

Code of Federal Regulations, 2012 CFR

2012-10-01

.... (iv) The manufacturer of the BWMS must demonstrate by using mathematical modeling, computational fluid dynamics modeling, and/or by calculations, that any downscaling will not affect the ultimate functioning... mathematical and computational fluid dynamics modeling) must be clearly identified in the Experimental Design...

46 CFR 162.060-26 - Land-based testing requirements.

Code of Federal Regulations, 2014 CFR

2014-10-01

.... (iv) The manufacturer of the BWMS must demonstrate by using mathematical modeling, computational fluid dynamics modeling, and/or by calculations, that any downscaling will not affect the ultimate functioning... mathematical and computational fluid dynamics modeling) must be clearly identified in the Experimental Design...

46 CFR 162.060-26 - Land-based testing requirements.

Code of Federal Regulations, 2013 CFR

2013-10-01

.... (iv) The manufacturer of the BWMS must demonstrate by using mathematical modeling, computational fluid dynamics modeling, and/or by calculations, that any downscaling will not affect the ultimate functioning... mathematical and computational fluid dynamics modeling) must be clearly identified in the Experimental Design...

Dynamics of sea level rise and coastal flooding on a changing landscape

NASA Astrophysics Data System (ADS)

Bilskie, M. V.; Hagen, S. C.; Medeiros, S. C.; Passeri, D. L.

2014-02-01

Standard approaches to determining the impacts of sea level rise (SLR) on storm surge flooding employ numerical models reflecting present conditions with modified sea states for a given SLR scenario. In this study, we advance this paradigm by adjusting the model framework so that it reflects not only a change in sea state but also variations to the landscape (morphologic changes and urbanization of coastal cities). We utilize a numerical model of the Mississippi and Alabama coast to simulate the response of hurricane storm surge to changes in sea level, land use/land cover, and land surface elevation for past (1960), present (2005), and future (2050) conditions. The results show that the storm surge response to SLR is dynamic and sensitive to changes in the landscape. We introduce a new modeling framework that includes modification of the landscape when producing storm surge models for future conditions.

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.

Evaluation of Dynamic Coastal Response to Sea-level Rise Modifies Inundation Likelihood

NASA Technical Reports Server (NTRS)

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments, making assessments of SLR-induced hazards essential for informed decision making. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30x30m resolution predictions for more than 38,000 sq km of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Assessment of dynamic effects on aircraft design loads: The landing impact case

NASA Astrophysics Data System (ADS)

Bronstein, Michael; Feldman, Esther; Vescovini, Riccardo; Bisagni, Chiara

2015-10-01

This paper addresses the potential benefits due to a fully dynamic approach to determine the design loads of a mid-size business jet. The study is conducted by considering the fuselage midsection of the DAEDALOS aircraft model with landing impact conditions. The comparison is presented in terms of stress levels between the novel dynamic approach and the standard design practice based on the use of equivalent static loads. The results illustrate that a slight reduction of the load levels can be achieved, but careful modeling of the damping level is needed. Guidelines for an improved load definition are discussed, and suggestions for future research activities are provided.

Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Yin, Runsheng; Li, Zhengpeng; Deng, Yulin; Tan, Kun; Deng, Xiangzheng; Rothstein, David; Qi, Jiaguo

2010-01-01

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon budgets. Here we use the General Ensemble biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China’s upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to a lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sink/source patterns showed a high degree of spatial heterogeneity. Carbon sinks were associated with forest areas without disturbances, whereas carbon sources were primarily caused by stand-replacing disturbances. It is critical to adequately represent the detailed fast-changing dynamics of land use activities in regional biogeochemical models to determine the spatial and temporal evolution of regional carbon sink/source patterns.

Coupled impacts of climate and land use change across a river-lake continuum: insights from an integrated assessment model of Lake Champlain’s Missisquoi Basin, 2000-2040

NASA Astrophysics Data System (ADS)

Zia, Asim; Bomblies, Arne; Schroth, Andrew W.; Koliba, Christopher; Isles, Peter D. F.; Tsai, Yushiou; Mohammed, Ibrahim N.; Bucini, Gabriela; Clemins, Patrick J.; Turnbull, Scott; Rodgers, Morgan; Hamed, Ahmed; Beckage, Brian; Winter, Jonathan; Adair, Carol; Galford, Gillian L.; Rizzo, Donna; Van Houten, Judith

2016-11-01

Global climate change (GCC) is projected to bring higher-intensity precipitation and higher-variability temperature regimes to the Northeastern United States. The interactive effects of GCC with anthropogenic land use and land cover changes (LULCCs) are unknown for watershed level hydrological dynamics and nutrient fluxes to freshwater lakes. Increased nutrient fluxes can promote harmful algal blooms, also exacerbated by warmer water temperatures due to GCC. To address the complex interactions of climate, land and humans, we developed a cascading integrated assessment model to test the impacts of GCC and LULCC on the hydrological regime, water temperature, water quality, bloom duration and severity through 2040 in transnational Lake Champlain’s Missisquoi Bay. Temperature and precipitation inputs were statistically downscaled from four global circulation models (GCMs) for three Representative Concentration Pathways. An agent-based model was used to generate four LULCC scenarios. Combined climate and LULCC scenarios drove a distributed hydrological model to estimate river discharge and nutrient input to the lake. Lake nutrient dynamics were simulated with a 3D hydrodynamic-biogeochemical model. We find accelerated GCC could drastically limit land management options to maintain water quality, but the nature and severity of this impact varies dramatically by GCM and GCC scenario.

Impacts of urbanization on carbon balance in terrestrial ecosystems of the Southern United States.

PubMed

Zhang, Chi; Tian, Hanqin; Chen, Guangsheng; Chappelka, Arthur; Xu, Xiaofeng; Ren, Wei; Hui, Dafeng; Liu, Mingliang; Lu, Chaoqun; Pan, Shufen; Lockaby, Graeme

2012-05-01

Using a process-based Dynamic Land Ecosystem Model, we assessed carbon dynamics of urbanized/developed lands in the Southern United States during 1945-2007. The results indicated that approximately 1.72 (1.69-1.77) Pg (1P = 10(15)) carbon was stored in urban/developed lands, comparable to the storage of shrubland or cropland in the region. Urbanization resulted in a release of 0.21 Pg carbon to the atmosphere during 1945-2007. Pre-urbanization vegetation type and time since land conversion were two primary factors determining the extent of urbanization impacts on carbon dynamics. After a rapid decline of carbon storage during land conversion, an urban ecosystem gradually accumulates carbon and may compensate for the initial carbon loss in 70-100 years. The carbon sequestration rate of urban ecosystem diminishes with time, nearly disappearing in two centuries after land conversion. This study implied that it is important to take urbanization effect into account for assessing regional carbon balance. Published by Elsevier Ltd.

Characteristics of organic soil in black spruce forests: implications for the application of land surface and ecosystem models in cold regions

Treesearch

Shuhua Yi; Kristen Manies; Jennifer Harden; David McGuire

2009-01-01

Soil organic layers (OL) play an important role in land-atmosphere exchanges of water, energy and carbon in cold environments. The proper implementation of OL in land surface and ecosystem models is important for predicting dynamic responses to climate warming. Based on the analysis of OL samples of black spruce (Picea mariana), we recommend that...

A spatial-temporal system for dynamic cadastral management.

PubMed

Nan, Liu; Renyi, Liu; Guangliang, Zhu; Jiong, Xie

2006-03-01

A practical spatio-temporal database (STDB) technique for dynamic urban land management is presented. One of the STDB models, the expanded model of Base State with Amendments (BSA), is selected as the basis for developing the dynamic cadastral management technique. Two approaches, the Section Fast Indexing (SFI) and the Storage Factors of Variable Granularity (SFVG), are used to improve the efficiency of the BSA model. Both spatial graphic data and attribute data, through a succinct engine, are stored in standard relational database management systems (RDBMS) for the actual implementation of the BSA model. The spatio-temporal database is divided into three interdependent sub-databases: present DB, history DB and the procedures-tracing DB. The efficiency of database operation is improved by the database connection in the bottom layer of the Microsoft SQL Server. The spatio-temporal system can be provided at a low-cost while satisfying the basic needs of urban land management in China. The approaches presented in this paper may also be of significance to countries where land patterns change frequently or to agencies where financial resources are limited.

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

NASA Astrophysics Data System (ADS)

Cai, X.; Yang, Z.-L.; Fisher, J. B.; Zhang, X.; Barlage, M.; Chen, F.

2016-01-01

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station - a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

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.

When and where to move: Dynamic occupancy models explain the range dynamics of a food nomadic bird under climate and land cover change.

PubMed

Kalle, Riddhika; Ramesh, Tharmalingam; Downs, Colleen T

2018-01-01

Globally, long-term research is critical to monitor the responses of tropical species to climate and land cover change at the range scale. Citizen science surveys can reveal the long-term persistence of poorly known nomadic tropical birds occupying fragmented forest patches. We applied dynamic occupancy models to 13 years (2002-2014) of citizen science-driven presence/absence data on Cape parrot (Poicephalus robustus), a food nomadic bird endemic to South Africa. We modeled its underlying range dynamics as a function of resource distribution, and change in climate and land cover through the estimation of colonization and extinction patterns. The range occupancy of Cape parrot changed little over time (ψ = 0.75-0.83) because extinction was balanced by recolonization. Yet, there was considerable regional variability in occupancy and detection probability increased over the years. Colonizations increased with warmer temperature and area of orchards, thus explaining their range shifts southeastwards in recent years. Although colonizations were higher in the presence of nests and yellowwood trees (Afrocarpus and Podocarpus spp.), the extinctions in small forest patches (≤227 ha) and during low precipitation (≤41 mm) are attributed to resource constraints and unsuitable climatic conditions. Loss of indigenous forest cover and artificial lake/water bodies increased extinction probabilities of Cape parrot. The land use matrix (fruit farms, gardens, and cultivations) surrounding forest patches provides alternative food sources, thereby facilitating spatiotemporal colonization and extinction in the human-modified matrix. Our models show that Cape parrots are vulnerable to extreme climatic conditions such as drought which is predicted to increase under climate change. Therefore, management of optimum sized high-quality forest patches is essential for long-term survival of Cape parrot populations. Our novel application of dynamic occupancy models to long-term citizen science monitoring data unfolds the complex relationships between the environmental dynamics and range fluctuations of this food nomadic species. © 2017 John Wiley & Sons Ltd.

Research on Land Use Changes in Panjin City Basing on Remote Sensing Data

NASA Astrophysics Data System (ADS)

Ding, Hua; Li, Ru Ren; Shuang Sun, Li; Wang, Xin; Liu, Yu Mei

2018-05-01

Taking Landsat remote sensing image as the main data source, the research on land use changes in Panjin City in 2005 to 2015 is made with the support of remote sensing platform and GIS platform in this paper; the range of land use changes and change rate are analyzed through the classification of remote sensing image; the dynamic analysis on land changes is made with the help of transfer matrix of land use type; the quantitative calculation on all kinds of dynamic change features of land changes is made by utilizing mathematical model; and the analysis on driving factors of land changes of image is made at last. The research results show that, in recent ten years, the area of cultivated land in Panjin City decreased, the area of vegetation increased, and meanwhile the area of road increased drastically, the settlement place decreased than ever, and water area changed slightly.

The Effect of Afterbody Length of the Hydrodynamic Stability of a Dynamic Model of a Flying Boat: Langley Tank Model 134

NASA Technical Reports Server (NTRS)

Land, Norman S

1945-01-01

A program of model tests has been completed at Langley tank no. 1 which will furnish a qualitative guide as to the relation of length of afterbody and depth of step. The model used for the tests was a l/12-size unpowered dynamic model of a hypothetical 160,000-pound airplane. The results showed that an increase in length of afterbody requires an accompanying increase in depth of step to maintain adequate landing stability. Changing the length of afterbody and depth of step in such a manner as to maintain a given landing stability will result in only small changes in take-off stability.

Sensitivity of Precipitation in Coupled Land-Atmosphere Models

NASA Technical Reports Server (NTRS)

Neelin, David; Zeng, N.; Suarez, M.; Koster, R.

2004-01-01

The project objective was to understand mechanisms by which atmosphere-land-ocean processes impact precipitation in the mean climate and interannual variations, focusing on tropical and subtropical regions. A combination of modeling tools was used: an intermediate complexity land-atmosphere model developed at UCLA known as the QTCM and the NASA Seasonal-to-Interannual Prediction Program general circulation model (NSIPP GCM). The intermediate complexity model was used to develop hypotheses regarding the physical mechanisms and theory for the interplay of large-scale dynamics, convective heating, cloud radiative effects and land surface feedbacks. The theoretical developments were to be confronted with diagnostics from the more complex GCM to validate or modify the theory.

Modeling vulnerability to thermokarst disturbance and its consequences on regional land cover dynamic in boreal Alaska

NASA Astrophysics Data System (ADS)

Genet, H.; Lara, M. J.; Bolton, W. R.; McGuire, A. D.

2016-12-01

Estimation of the magnitude and consequences of permafrost degradation in high latitude is one of the most urgent research challenges related to contemporary and future climate change. In addition to widespread vertical degradation, ice-rich permafrost can thaw laterally, often triggering abrupt subsidence of the ground surface called thermokart. In this depression, permafrost plateau vegetation will transition to wetlands or lakes, while surface water of the surrounding landscape may drain towards it. These abrupt changes in land cover and hydrology can have dramatic consequences from wildlife habitat and biogeochemical cycles. Although recent studies have documented an acceleration of the rates of thermokarst formation in boreal and arctic peatlands, the importance of thermokarst at the regional level is still poorly understood. To better understand the vulnerability of the landscape to thermokarst disturbance in Alaska, we developed the Alaska Thermokarst Model (ATM), a state-and-transition model designed to simulate land cover change associated with thermokarst disturbance. In boreal regions, the model simulates transitions from permafrost plateau forest to thermokarst lake, bog or fen, as a function of climate and fire dynamics, permafrost characteristics and physiographic information. This model is designed and parameterized based on existing literature and a new repeated imagery analysis we conducted in a major wetland complex in boreal Alaska. We will present simulation and validation of thermokarst dynamic and associated land cover change in two wetland complexes in boreal Alaska, from 2000 to 2100 for six climate scenarios associating three AR5 emission scenarios and two global circulation model simulations. By 2100, ATM is predicting decrease between 3.5 and 9.1 % in the extent of permafrost plateau forest, mostly to the benefit of thermokarst fen, and lake. This analysis allowed us to assess the importance of thermokarst dynamics and landscape evolution associated with permafrost thaw in vulnerable regions of boreal Alaska during the 21st century and could be used as a baseline for managers to incorporate projected land cover changes in designing land management strategies.

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

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 interplay of climate and land use change affects the distribution of EU bumblebees.

PubMed

Marshall, Leon; Biesmeijer, Jacobus C; Rasmont, Pierre; Vereecken, Nicolas J; Dvorak, Libor; Fitzpatrick, Una; Francis, Frédéric; Neumayer, Johann; Ødegaard, Frode; Paukkunen, Juho P T; Pawlikowski, Tadeusz; Reemer, Menno; Roberts, Stuart P M; Straka, Jakub; Vray, Sarah; Dendoncker, Nicolas

2018-01-01

Bumblebees in Europe have been in steady decline since the 1900s. This decline is expected to continue with climate change as the main driver. However, at the local scale, land use and land cover (LULC) change strongly affects the occurrence of bumblebees. At present, LULC change is rarely included in models of future distributions of species. This study's objective is to compare the roles of dynamic LULC change and climate change on the projected distribution patterns of 48 European bumblebee species for three change scenarios until 2100 at the scales of Europe, and Belgium, Netherlands and Luxembourg (BENELUX). We compared three types of models: (1) only climate covariates, (2) climate and static LULC covariates and (3) climate and dynamic LULC covariates. The climate and LULC change scenarios used in the models include, extreme growth applied strategy (GRAS), business as might be usual and sustainable European development goals. We analysed model performance, range gain/loss and the shift in range limits for all bumblebees. Overall, model performance improved with the introduction of LULC covariates. Dynamic models projected less range loss and gain than climate-only projections, and greater range loss and gain than static models. Overall, there is considerable variation in species responses and effects were most pronounced at the BENELUX scale. The majority of species were predicted to lose considerable range, particularly under the extreme growth scenario (GRAS; overall mean: 64% ± 34). Model simulations project a number of local extinctions and considerable range loss at the BENELUX scale (overall mean: 56% ± 39). Therefore, we recommend species-specific modelling to understand how LULC and climate interact in future modelling. The efficacy of dynamic LULC change should improve with higher thematic and spatial resolution. Nevertheless, current broad scale representations of change in major land use classes impact modelled future distribution patterns. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Object view in spatial system dynamics: a grassland farming example

PubMed Central

Neuwirth, Christian; Hofer, Barbara; Schaumberger, Andreas

2016-01-01

Abstract Spatial system dynamics (SSD) models are typically implemented by linking stock variables to raster grids while the use of object representations of human artefacts such as buildings or ownership has been limited. This limitation is addressed by this article, which demonstrates the use of object representations in SSD. The objects are parcels of land that are attributed to grassland farms. The model simulates structural change in agriculture, i.e., change in the size of farms. The aim of the model is to reveal relations between structural change, farmland fragmentation and variable farmland quality. Results show that fragmented farms tend to become consolidated by structural change, whereas consolidated initial conditions result in a significant increase of fragmentation. Consolidation is reinforced by a dynamic land market and high transportation costs. The example demonstrates the capabilities of the object-based approach for integrating object geometries (parcel shapes) and relations between objects (distances between parcels) dynamically in SSD. PMID:28190972

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

Representing anthropogenic gross land use change, wood harvest, and forest age dynamics in a global vegetation model ORCHIDEE-MICT v8.4.2

NASA Astrophysics Data System (ADS)

Yue, Chao; Ciais, Philippe; Luyssaert, Sebastiaan; Li, Wei; McGrath, Matthew J.; Chang, Jinfeng; Peng, Shushi

2018-01-01

Land use change (LUC) is among the main anthropogenic disturbances in the global carbon cycle. Here we present the model developments in a global dynamic vegetation model ORCHIDEE-MICT v8.4.2 for a more realistic representation of LUC processes. First, we included gross land use change (primarily shifting cultivation) and forest wood harvest in addition to net land use change. Second, we included sub-grid evenly aged land cohorts to represent secondary forests and to keep track of the transient stage of agricultural lands since LUC. Combination of these two features allows the simulation of shifting cultivation with a rotation length involving mainly secondary forests instead of primary ones. Furthermore, a set of decision rules regarding the land cohorts to be targeted in different LUC processes have been implemented. Idealized site-scale simulation has been performed for miombo woodlands in southern Africa assuming an annual land turnover rate of 5 % grid cell area between forest and cropland. The result shows that the model can correctly represent forest recovery and cohort aging arising from agricultural abandonment. Such a land turnover process, even though without a net change in land cover, yields carbon emissions largely due to the imbalance between the fast release from forest clearing and the slow uptake from agricultural abandonment. The simulation with sub-grid land cohorts gives lower emissions than without, mainly because the cleared secondary forests have a lower biomass carbon stock than the mature forests that are otherwise cleared when sub-grid land cohorts are not considered. Over the region of southern Africa, the model is able to account for changes in different forest cohort areas along with the historical changes in different LUC activities, including regrowth of old forests when LUC area decreases. Our developments provide possibilities to account for continental or global forest demographic change resulting from past anthropogenic and natural disturbances.

The Joint UK Land Environment Simulator (JULES), model description - Part 2: Carbon fluxes and vegetation dynamics

NASA Astrophysics Data System (ADS)

Clark, D. B.; Mercado, L. M.; Sitch, S.; Jones, C. D.; Gedney, N.; Best, M. J.; Pryor, M.; Rooney, G. G.; Essery, R. L. H.; Blyth, E.; Boucher, O.; Harding, R. J.; Huntingford, C.; Cox, P. M.

2011-09-01

The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Many studies have demonstrated the important role of the land surface in the functioning of the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of climate change, increasing atmospheric carbon dioxide concentrations, changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. This paper describes the consolidation of these advances in the modelling of carbon fluxes and stores, in both the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.

Challenges in Global Land Use/Land Cover Change Modeling

NASA Astrophysics Data System (ADS)

Clarke, K. C.

2011-12-01

For the purposes of projecting and anticipating human-induced land use change at the global scale, much work remains in the systematic mapping and modeling of world-wide land uses and their related dynamics. In particular, research has focused on tropical deforestation, loss of prime agricultural land, loss of wild land and open space, and the spread of urbanization. Fifteen years of experience in modeling land use and land cover change at the regional and city level with the cellular automata model SLEUTH, including cross city and regional comparisons, has led to an ability to comment on the challenges and constraints that apply to global level land use change modeling. Some issues are common to other modeling domains, such as scaling, earth geometry, and model coupling. Others relate to geographical scaling of human activity, while some are issues of data fusion and international interoperability. Grid computing now offers the prospect of global land use change simulation. This presentation summarizes what barriers face global scale land use modeling, but also highlights the benefits of such modeling activity on global change research. An approach to converting land use maps and forecasts into environmental impact measurements is proposed. Using such an approach means that multitemporal mapping, often using remotely sensed sources, and forecasting can also yield results showing the overall and disaggregated status of the environment.

Simulation of land use change in the three gorges reservoir area based on CART-CA

NASA Astrophysics Data System (ADS)

Yuan, Min

2018-05-01

This study proposes a new method to simulate spatiotemporal complex multiple land uses by using classification and regression tree algorithm (CART) based CA model. In this model, we use classification and regression tree algorithm to calculate land class conversion probability, and combine neighborhood factor, random factor to extract cellular transformation rules. The overall Kappa coefficient is 0.8014 and the overall accuracy is 0.8821 in the land dynamic simulation results of the three gorges reservoir area from 2000 to 2010, and the simulation results are satisfactory.

The role of groundwater in hydrological processes and memory

NASA Astrophysics Data System (ADS)

Lo, Min-Hui

The interactions between soil moisture and groundwater play important roles in controlling Earth's climate, by changing the terrestrial water cycle. However, most contemporary land surface models (LSMs) used for climate modeling lack any representation of groundwater aquifers. In this dissertation, the effects of water table dynamics on the National Center for Atmospheric Research (NCAR) Community Land Model (CLM) and Community Atmosphere Model (CAM) hydrology and land-atmosphere simulations are investigated. First, a simple, lumped unconfined aquifer model is incorporated into the CLM, in which the water table is interactively coupled to the soil moisture through groundwater recharge fluxes. The recent availability of GRACE water storage data provides a unique opportunity to constrain LSMs simulations of terrestrial hydrology. A multi-objective calibration framework using GRACE and streamflow data is developed. This approach improves parameter estimation and reduces the uncertainty of water table simulations in the CLM. Next, experiments are conducted with the off-line CLM to explore the effects of groundwater on land surface memory. Results show that feedbacks of groundwater on land surface memory can be positive, negative, or neutral depending on water table dynamics. The CAM-CLM is further utilized to investigate the effects of water table dynamics on spatial-temporal variations of precipitation. Results indicate that groundwater can increase short-term (seasonal) and long-term (interannual) memory of precipitation for some regions with suitable groundwater table depth. Finally, lower tropospheric water vapor is increased due to the presence of groundwater in the model. However, the impact of groundwater on the spatial distribution of precipitation is not globally homogeneous. In the boreal summer, tropical land regions show a positive (negative) anomaly over the Northern (Southern) Hemisphere. The increased tropical precipitation follows the climatology of the convective zone rather than that of evapotranspiration. In contrast, evapotranspiration is the major contribution to the increased precipitation in the transition climatic zone (e.g., Central North America), where the land and atmosphere are strongly coupled. This dissertation reveals the highly nonlinear responses of precipitation and soil moisture to the groundwater representation in the model, and also underscores the importance of subsurface hydrological memory processes in the climate system.

Integrated dynamic landscape analysis and modeling system (IDLAMS) : installation manual.

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

Li, Z.; Majerus, K. A.; Sundell, R. C.

The Integrated Dynamic Landscape Analysis and Modeling System (IDLAMS) is a prototype, integrated land management technology developed through a joint effort between Argonne National Laboratory (ANL) and the US Army Corps of Engineers Construction Engineering Research Laboratories (USACERL). Dr. Ronald C. Sundell, Ms. Pamela J. Sydelko, and Ms. Kimberly A. Majerus were the principal investigators (PIs) for this project. Dr. Zhian Li was the primary software developer. Dr. Jeffrey M. Keisler, Mr. Christopher M. Klaus, and Mr. Michael C. Vogt developed the decision analysis component of this project. It was developed with funding support from the Strategic Environmental Research andmore » Development Program (SERDP), a land/environmental stewardship research program with participation from the US Department of Defense (DoD), the US Department of Energy (DOE), and the US Environmental Protection Agency (EPA). IDLAMS predicts land conditions (e.g., vegetation, wildlife habitats, and erosion status) by simulating changes in military land ecosystems for given training intensities and land management practices. It can be used by military land managers to help predict the future ecological condition for a given land use based on land management scenarios of various levels of training intensity. It also can be used as a tool to help land managers compare different land management practices and further determine a set of land management activities and prescriptions that best suit the needs of a specific military installation.« less

Influence of Land Cover Heterogeneity, Land-Use Change and Management on the Regional Carbon Cycle in the Upper Midwest USA as Evaluated by High-Density Observations and a Dynamic Ecosystem Model

NASA Astrophysics Data System (ADS)

Desai, A. R.; Bolstad, P. V.; Moorcroft, P. R.; Davis, K. J.

2005-12-01

The interplay between land use change, forest management and land cover variability complicates the ability to characterize regional scale (10-1000 km) exchange of carbon dioxide between the land surface and atmosphere in heterogeneous landscapes. An attempt was made to observe and model these factors and their influence on the regional carbon cycle across the upper Midwest USA. A high density of eddy-covariance carbon flux, micrometeorology, carbon dioxide mixing ratio, stand-scale biometry and canopy component flux observations have been occurring in this area as part of the Chequamegon Ecosystem-Atmosphere Study. Observations limited to sampling only dominant stands and coarse-resolution biogeochemical models limited to biome-scale parameterization neither accurately capture the variability of carbon fluxes measured by the network of eddy covariance towers nor match the regional-scale carbon flux inferred from very tall tower eddy covariance measurements and multi-site upscaling. Analysis of plot level biometric data, U.S. Forest Service Forest Inventory Analysis data and high-resolution land cover data around the tall tower revealed significant variations in vegetation type, stand age, canopy stocking and structure. Wetlands, clearcuts and recent natural disturbances occur in characteristic small non-uniformly distributed patches that aggregate to form more than 30% of the landscape. The Ecosystem Demography model, a dynamic ecosystem model that incorporates vegetation heterogeneity, canopy structure, stand age, disturbance, land use change and forest management, was parameterized with regional biometric data and meteorology, historical records of land management and high-resolution satellite land cover maps. The model will be used to examine the significance of past land use change, natural disturbance history and current forest management in explaining landscape structure and regional carbon fluxes observed in the region today.

Evidence of weak land-atmosphere coupling under varying bare soil conditions: Are fully coupled Darcy/Navier-Stokes models necessary for simulating soil moisture dynamics?

NASA Astrophysics Data System (ADS)

Illangasekare, T. H.; Trautz, A. C.; Howington, S. E.; Cihan, A.

2017-12-01

It is a well-established fact that the land and atmosphere form a continuum in which the individual domains are coupled by heat and mass transfer processes such as bare-soil evaporation. Soil moisture dynamics can be simulated at the representative elementary volume (REV) scale using decoupled and fully coupled Darcy/Navier-Stokes models. Decoupled modeling is an asynchronous approach in which flow and transport in the soil and atmosphere is simulated independently; the two domains are coupled out of time-step via prescribed flux parameterizations. Fully coupled modeling in contrast, solves the governing equations for flow and transport in both domains simultaneously with the use of coupling interface boundary conditions. This latter approach, while being able to provide real-time two-dimensional feedbacks, is considerably more complex and computationally intensive. In this study, we investigate whether fully coupled models are necessary, or if the simpler decoupled models can sufficiently capture soil moisture dynamics under varying land preparations. A series of intermediate-scale physical and numerical experiments were conducted in which soil moisture distributions and evaporation estimates were monitored at high spatiotemporal resolutions for different heterogeneous packing and soil roughness scenarios. All experimentation was conducted at the newly developed Center for Experimental Study of Subsurface Environmental Processes (CESEP) wind tunnel-porous media user test-facility at the Colorado School of. Near-surface atmospheric measurements made during the experiments demonstrate that the land-atmosphere coupling was relatively weak and insensitive to the applied edaphic and surface conditions. Simulations with a decoupled multiphase heat and mass transfer model similarly show little sensitivity to local variations in atmospheric forcing; a single, simple flux parameterization can sufficiently capture the soil moisture dynamics (evaporation and redistribution) as long as the subsurface conditions (i.e., heterogeneity) are properly described. These findings suggest that significant improvements to simulations results should not be expected if fully coupled modeling were adopted in scenarios of weak land-atmosphere coupling in the context of bare soil evaporation.

Land-cover impacts on streamflow: a change-detection modelling approach that incorporates parameter uncertainty

Treesearch

Jan Seibert; Jeffrey J. McDonnell

2010-01-01

The effect of land-use or land-cover change on stream runoff dynamics is not fully understood. In many parts of the world, forest management is the major land-cover change agent. While the paired catchment approach has been the primary methodology used to quantify such effects, it is only possible for small headwater catchments where there is uniformity in...

Forecasts of county-level land uses under three future scenarios: a technical document supporting the Forest Service 2010 RPA Assessment

Treesearch

David N. Wear

2011-01-01

Accurately forecasting future forest conditions and the implications for ecosystem services depends on understanding land use dynamics. In support of the 2010 Renewable Resources Planning Act (RPA) Assessment, we forecast changes in land uses for the coterminous United States in response to three scenarios. Our land use models forecast urbanization in response to the...

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

Treesearch

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

2017-01-01

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

Experimental and analytical dynamic flow characteristics of an axial-flow fan from an air cushion landing system model

NASA Technical Reports Server (NTRS)

Thompson, W. C.; Boghani, A. B.; Leland, T. J. W.

1977-01-01

An investigation was conducted to compare the steady-state and dynamic flow characteristics of an axial-flow fan which had been used previously as the air supply fan for some model air cushion landing system studies. Steady-state flow characteristics were determined in the standard manner by using differential orifice pressures for the flow regime from free flow to zero flow. In this same regime, a correlative technique was established so that fan inlet and outlet pressures could be used to measure dynamic flow as created by a rotating damper. Dynamic tests at damper frequencies up to 5 Hz showed very different flow characteristics when compared with steady-state flow, particularly with respect to peak pressures and the pressure-flow relationship at fan stall and unstall. A generalized, rational mathematical fan model was developed based on physical fan parameters and a steady-state flow characteristic. The model showed good correlation with experimental tests at damper frequencies up to 5 Hz.

Landscape-scale modelling of soil carbon dynamics under land use and climate change

NASA Astrophysics Data System (ADS)

Lacoste, Marine; Viaud, Valérie; Michot, Didier; Christian, Walter

2013-04-01

Soil organic carbon (SOC) sequestration is highly linked to soil use and farming practices, but also to soil redistributions, soil properties, and climate. In a global change context, landscape, farming practice and climate changes are expected; and they will most probably impact SOC dynamics. To assess their respective impacts, we modelled the SOC contents and stocks evolution at the scale of an agricultural landscape, by taking into account the soil redistribution by tillage and water processes. The simulations were conducted from 2010 to 2100 under different scenarios of landscape and climate. These scenarios combined different land uses associated to specific farming practices (mixed dairy with rotations of crops and grasslands, intensive cropping with only crops rotations or permanent grasslands), landscape managements (hedges planting or removal), and climates (business-as-usual climate and climate change, with temperature and precipitations increase). We used a spatially SOC dynamic model (adapted from RothC), coupled to a soil redistribution model (LandSoil). SOC dynamics were spatially modelled with a lateral resolution of 2-m and for soil organic layers up to 105 cm. Initial SOC stocks were described with a 2-m resolution map based on field data and produced with digital soil mapping methods. The major factor of change in SOC stocks was land use change, the second factor of importance was climate change, and finally landscape management: for the total SOC stocks (0-to-105 cm soil layer) the change of land use, climate and landscape management induced a respective mean absolute variation of 10 to 20 tC ha-1, 9 tC ha-1 and 0.4 tC ha-1. When considering the 0-to-105 cm soil layer, the different modelled landscapes showed the same sensitivity to climate change, with induced a mean decrease of 10 tC ha-1. However, the impact of climate change was found different according to the different modelled landscape when considering the 0-to-7.5 and 0-to-30 cm soil layers: the more sensitive landscapes were those of intensive cropping. This shows the importance of considering not only the plough layer, but also the vertical distribution of SOC stocks to assess the variation in SOC dynamics under land use, landscape management or climate change. Finally, rural hedgerow landscapes were proved to be quite well adapted for soil protection in a context of climate change, focusing on both carbon storage and soil erosion.

Interfacing geographic information systems and remote sensing for rural land-use analysis

NASA Technical Reports Server (NTRS)

Nellis, M. Duane; Lulla, Kamlesh; Jensen, John

1990-01-01

Recent advances in computer-based geographic information systems (GISs) are briefly reviewed, with an emphasis on the incorporation of remote-sensing data in GISs for rural applications. Topics addressed include sampling procedures for rural land-use analyses; GIS-based mapping of agricultural land use and productivity; remote sensing of land use and agricultural, forest, rangeland, and water resources; monitoring the dynamics of irrigation agriculture; GIS methods for detecting changes in land use over time; and the development of land-use modeling strategies.

Sustainable and Smart City Planning Using Spatial Data in Wallonia

NASA Astrophysics Data System (ADS)

Stephenne, N.; Beaumont, B.; Hallot, E.; Wolff, E.; Poelmans, L.; Baltus, C.

2016-09-01

Simulating population distribution and land use changes in space and time offer opportunities for smart city planning. It provides a holistic and dynamic vision of fast changing urban environment to policy makers. Impacts, such as environmental and health risks or mobility issues, of policies can be assessed and adapted consequently. In this paper, we suppose that "Smart" city developments should be sustainable, dynamic and participative. This paper addresses these three smart objectives in the context of urban risk assessment in Wallonia, Belgium. The sustainable, dynamic and participative solution includes (i) land cover and land use mapping using remote sensing and GIS, (ii) population density mapping using dasymetric mapping, (iii) predictive modelling of land use changes and population dynamics and (iv) risk assessment. The comprehensive and long-term vision of the territory should help to draw sustainable spatial planning policies, to adapt remote sensing acquisition, to update GIS data and to refine risk assessment from regional to city scale.

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.

Can future land use change be usefully predicted?

NASA Astrophysics Data System (ADS)

Ramankutty, N.; Coomes, O.

2011-12-01

There has been increasing recognition over the last decade that land use and land cover change is an important driver of global environmental change. Consequently, there have been growing efforts to understanding processes of land change from local-to-global scales, and to develop models to predict future changes in the land. However, we believe that such efforts are hampered by limited attention being paid to the critical points of land change. Here, we present a framework for understanding land use change by distinguishing within-regime land-use dynamics from land-use regime shifts. Illustrative historical examples reveal the significance of land-use regime shifts. We further argue that the land-use literature predominantly demonstrates a good understanding (with predictive power) of within-regime dynamics, while understanding of land-use regime shifts is limited to ex post facto explanations with limited predictive capability. The focus of land use change science needs to be redirected toward studying land-use regime shifts if we are to have any hope of making useful future projections. We present a preliminary framework for understanding land-use regime-shifts, using two case studies in Latin America as examples. We finally discuss the implications of our proposal for land change science.

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

DOE PAGES

Cai, X.; Yang, Z. -L.; Fisher, J. B.; ...

2016-01-15

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

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

Cai, X.; Yang, Z. -L.; Fisher, J. B.

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. Here in this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soilmore » and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.« less

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

A Systematic Evaluation of Noah-MP in Simulating Land-Atmosphere Energy, Water, and Carbon Exchanges Over the Continental United States

NASA Astrophysics Data System (ADS)

Ma, Ning; Niu, Guo-Yue; Xia, Youlong; Cai, Xitian; Zhang, Yinsheng; Ma, Yaoming; Fang, Yuanhao

2017-11-01

Accurate simulation of energy, water, and carbon fluxes exchanging between the land surface and the atmosphere is beneficial for improving terrestrial ecohydrological and climate predictions. We systematically assessed the Noah land surface model (LSM) with mutiparameterization options (Noah-MP) in simulating these fluxes and associated variations in terrestrial water storage (TWS) and snow cover fraction (SCF) against various reference products over 18 United States Geological Survey two-digital hydrological unit code regions of the continental United States (CONUS). In general, Noah-MP captures better the observed seasonal and interregional variability of net radiation, SCF, and runoff than other variables. With a dynamic vegetation model, it overestimates gross primary productivity by 40% and evapotranspiration (ET) by 22% over the whole CONUS domain; however, with a prescribed climatology of leaf area index, it greatly improves ET simulation with relative bias dropping to 4%. It accurately simulates regional TWS dynamics in most regions except those with large lakes or severely affected by irrigation and/or impoundments. Incorporating the lake water storage variations into the modeled TWS variations largely reduces the TWS simulation bias more obviously over the Great Lakes with model efficiency increasing from 0.18 to 0.76. Noah-MP simulates runoff well in most regions except an obvious overestimation (underestimation) in the Rio Grande and Lower Colorado (New England). Compared with North American Land Data Assimilation System Phase 2 (NLDAS-2) LSMs, Noah-MP shows a better ability to simulate runoff and a comparable skill in simulating Rn but a worse skill in simulating ET over most regions. This study suggests that future model developments should focus on improving the representations of vegetation dynamics, lake water storage dynamics, and human activities including irrigation and impoundments.

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

USGS Publications Warehouse

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments1, 2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolution predictions for more than 38,000 km2 of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Carbon emissions risk map from deforestation in the tropical Amazon

NASA Astrophysics Data System (ADS)

Ometto, J.; Soler, L. S.; Assis, T. D.; Oliveira, P. V.; Aguiar, A. P.

2011-12-01

Assis, Pedro Valle This work aims to estimate the carbon emissions from tropical deforestation in the Brazilian Amazon associated to the risk assessment of future land use change. The emissions are estimated by incorporating temporal deforestation dynamics, accounting for the biophysical and socioeconomic heterogeneity in the region, as well secondary forest growth dynamic in abandoned areas. The land cover change model that supported the risk assessment of deforestation, was run based on linear regressions. This method takes into account spatial heterogeneity of deforestation as the spatial variables adopted to fit the final regression model comprise: environmental aspects, economic attractiveness, accessibility and land tenure structure. After fitting a suitable regression models for each land cover category, the potential of each cell to be deforested (25x25km and 5x5 km of resolution) in the near future was used to calculate the risk assessment of land cover change. The carbon emissions model combines high-resolution new forest clear-cut mapping and four alternative sources of spatial information on biomass distribution for different vegetation types. The risk assessment map of CO2 emissions, was obtained by crossing the simulation results of the historical land cover changes to a map of aboveground biomass contained in the remaining forest. This final map represents the risk of CO2 emissions at 25x25km and 5x5 km until 2020, under a scenario of carbon emission reduction target.

Analysing spatio-temporal land degradation dynamics in dry rangelands using landscape metrics and satellite time series data

NASA Astrophysics Data System (ADS)

von Keyserlingk, Jennifer; Paton, Eva Nora; Förster, Saskia; Bronstert, Axel

2017-04-01

Many of the dry rangelands of Southern Europe are threatened by land degradation. This process not only reduces the land's ecological functioning, but also its capacity to provide ecosystem goods and services for local land users. In rangelands, one important aspect is vegetation degradation, which reduces the land's capacity to support livestock. Thus, there is an urgent need to understand the complex dynamics and drivers of land degradation. In the past, both have been difficult to study due to the extensive spatial and temporal scales involved. In the last decade, a large number of remotely sensed imageries has become available for free, which enables a new approach to this topic. The aim of this research is to study land degradation as a multidimensional process incorporating its spatial and temporal components. We developed a methodological approach that makes use of long-term satellite Landsat data. Here, we use imagery of a typical degraded Mediterranean rangeland in Southern Cyprus (Randi Forest) for the years 1998-2015. We have chosen the NDVI as a proxy for vegetation greenness and applied different spatial landscape metrics to calculate changes in vegetation patterns over time. Further, we applied a time-series based approach (BFAST) on selected pixels, to look for sudden changes and trends in the vegetation dynamics. The results promoted our knowledge on how land degradation dynamics in Mediterranean rangelands can be captured through spatio-temporal vegetation dynamics and allowed us to select the most suitable metrics for further analysis. In the long-term, we aim at using Landsat satellite data covering 30 years. To gain a functional understanding of land degradation, we want to overlay our results from the remotely sensed data with results of an eco-hydrological model (SWAT).

An Overview of Landing Gear Dynamics

NASA Technical Reports Server (NTRS)

Pritchard, Jocelyn I.

1999-01-01

One of the problems facing the aircraft community is landing gear dynamics, especially shimmy and brake-induced vibration. Shimmy and brake-induced vibrations can lead to accidents due to excessive wear and shortened life of gear parts and contribute to pilot and passenger discomfort. To increase understanding of these problems, a literature survey was performed. The major focus is on work from the last ten years. Some older publications are included to understand the longevity of the problem and the background from earlier researchers. The literature survey includes analyses, testing, modeling, and simulation of aircraft landing gear; and experimental validation and characterization of shimmy and brake-induced vibration of aircraft landing gear. The paper presents an overview of the problem, background information, and a history of landing gear dynamics problems and solutions. Based on the survey an assessment and recommendations of the most critically needed enhancements to the state of the art will be presented. The status of Langley work contributing to this activity will be given.

CHALLENGES AND SUCCESSES MODELING THE INFLUENCES OF LAND USE CHANGES ON MERCURY DYNAMICS

EPA Science Inventory

Linked sets of atmospheric, watershed, water body, and food web models and supporting data are required to evaluate the effectiveness of proposals to regulate atmospheric mercury emissions. Simulating mercury dynamics in watersheds is a key step linking changes in atmospheric de...

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

USGS Publications Warehouse

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

2008-01-01

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

Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Famiglietti, J. S.; Wood, Eric F.

1993-01-01

A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.

Potential role of vegetation dynamics on recent extreme droughts over tropical South America

NASA Astrophysics Data System (ADS)

Wang, G.; Erfanian, A.; Fomenko, L.

2017-12-01

Tropical South America is a drought hot spot. In slightly over a decade (2005-2016), the region encountered three extreme droughts (2005, 2010, and 2016). Recurrent extreme droughts not only impact the region's eco-hydrology and socio-economy, but are also globally important as they can transform the planet's largest rainforest, the Amazon, from a carbon sink to a carbon source. Understanding drought drivers and mechanisms underlying extreme droughts in tropical South America can help better project the fate of the Amazon rainforest in a changing climate. In this study we use a regional climate model (RegCM4.3.4) coupled with a comprehensive land-surface model (CLM4.5) to study the present-day hydroclimate of the region, focusing specifically on what might have caused the frequent recurrence of extreme droughts. In the context of observation natural variability of the global oceanic forcing, we tackle the role of land-atmosphere interactions and ran the model with and without dynamic vegetation to study how vegetation dynamics and carbon-nitrogen cycles may have influenced the drought characteristics. Our results demonstrate skillful simulation of the South American climate in the model, and indicate substantial sensitivity of the region's hydroclimatology to vegetation dynamics. This presentation will compare the role of global oceanic forcing versus regional land surface feedback in the recent recurrent droughts, and will characterize the effects of vegetation dynamics in enhancing the drought severity. Preliminary results on future projections of the regional ecosystem and droughts perspective will be also presented.

A multiscale, hierarchical model of pulse dynamics in arid-land ecosystems

USGS Publications Warehouse

Collins, Scott L.; Belnap, Jayne; Grimm, N. B.; Rudgers, J. A.; Dahm, Clifford N.; D'Odorico, P.; Litvak, M.; Natvig, D. O.; Peters, Douglas C.; Pockman, W. T.; Sinsabaugh, R. L.; Wolf, B. O.

2014-01-01

Ecological processes in arid lands are often described by the pulse-reserve paradigm, in which rain events drive biological activity until moisture is depleted, leaving a reserve. This paradigm is frequently applied to processes stimulated by one or a few precipitation events within a growing season. Here we expand the original framework in time and space and include other pulses that interact with rainfall. This new hierarchical pulse-dynamics framework integrates space and time through pulse-driven exchanges, interactions, transitions, and transfers that occur across individual to multiple pulses extending from micro to watershed scales. Climate change will likely alter the size, frequency, and intensity of precipitation pulses in the future, and arid-land ecosystems are known to be highly sensitive to climate variability. Thus, a more comprehensive understanding of arid-land pulse dynamics is needed to determine how these ecosystems will respond to, and be shaped by, increased climate variability.

Heave-pitch-roll analysis and testing of air cushion landing systems

NASA Technical Reports Server (NTRS)

Boghani, A. B.; Captain, K. M.; Wormley, D. N.

1978-01-01

The analytical tools (analysis and computer simulation) needed to explain and predict the dynamic operation of air cushion landing systems (ACLS) is described. The following tasks were performed: the development of improved analytical models for the fan and the trunk; formulation of a heave pitch roll analysis for the complete ACLS; development of a general purpose computer simulation to evaluate landing and taxi performance of an ACLS equipped aircraft; and the verification and refinement of the analysis by comparison with test data obtained through lab testing of a prototype cushion. Demonstration of simulation capabilities through typical landing and taxi simulation of an ACLS aircraft are given. Initial results show that fan dynamics have a major effect on system performance. Comparison with lab test data (zero forward speed) indicates that the analysis can predict most of the key static and dynamic parameters (pressure, deflection, acceleration, etc.) within a margin of a 10 to 25 percent.

The effects of changing land cover on streamflow simulation in Puerto Rico

Treesearch

A.E. Van Beusekom; L.E. Hay; R.J. Viger; W.A. Gould; J.A. Collazo; A. Henareh Khalyani

2014-01-01

This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from...

The interaction between land use change, sediment fluxes and carbon dynamics: evaluating an integrated soil-landscape model at the millennial time-scale.

NASA Astrophysics Data System (ADS)

Bouchoms, Samuel; Van Oost, Kristof; Vanacker, Veerle

2015-04-01

Soil-landscape modelling has received growing attention as it allows us to evaluate the interaction between earth surface and soil bio-physical processes. At the landscape scale, human-induced land use change has altered the balance between soil erosion and production, and largely modified sediment fluxes. Intensification in soil redistribution rates affects the interaction between soil chemical, physical and biological processes at the landscape scale. Here, we evaluate the SPEROS-LT model, a spatially explicit 3D model combining a dynamic representation of land use, soil erosion and deposition and the soil carbon cycle. We assess the impact of millennial-scale human-induced land use change on sediment fluxes and carbon dynamics in the Dijle catchement (central Belgium). The watershed has undergone a 3000 years continuous human-induced alteration of the vegetation covers for agricultural characterized by Our study is based on land use reconstructions for the last 3000 years, including massive deforestation for agriculture in Roman Times and the Middle Ages followed by urbanization in the last 150 years. Land use reconstructions rely on simple land use allocation rules based on slope gradients. SPEROS-LT is parametrized for erosion rates against available figures in the literature by changing the transport capacity and the transfer coefficient which defines the amount of flux transferred between different land uses. Carbon content profiles at steady state (i.e. without influence of erosion or deposition) are calibrated for each land use and for the first upper meter of soil by comparing modeled profiles to an averaged observed profiles in stable areas of the pedologic region. We present a model sensitivity analysis and a full validation of the predicted soil carbon storage (horizontally, i.e. in space, and vertically, i.e. with depth) using a large database of observational data. The results indicate (i) a good agreement of the erosion rates. Speros LT modeled erosion and export rates, both modern and averaged over the last millennium, fall into the published range. Mean erosion rate over the last 1000 years equals 4.6 t/ha over the entire catchment while the export rate is 1.2 t/ha. (ii) Carbon content in the erosion areas is well predicted for lower soil layers (from 20 to 80 cm) where no significant differences were found between observational and modeled C content. There is though a significant difference for the top soil where modeled mean is 0.92% compared to the 0.8% in observations. (iii) erosion and deposition's spatial patterns are relatively well represented: correspondence between erosion areas as extracted from the digital soil map and modeled erosion maps higher for slightly truncated areas than in high truncation areas (55% of the modeled erosions pixels correspond to a non-depositional area compared to 37%). Correspondence between the model and the soil map increases with the total deposition ranging from 19% to 30% Yet, the model overestimated the carbon content in depositional areas, where statistical differences between observed and modeled carbon amount were found for each soil layers. This indicates that other factors, not accounted for by the model, influence carbon turnover for these sites. They may have a different dynamic than eroding places, cycling carbon faster or transferring it quicker to higher depth. Overall, the results indicates that the model performs relatively well in predicting sediment fluxes and carbon amount on long time scale during transient simulation. They underline the importance of developing an integrated approach to understand the dynamic and interactions at the landscape scale.

Assessing land-use history for reporting on cropland dynamics - A case study using the Land-Parcel Identification System in Ireland

NASA Astrophysics Data System (ADS)

Zimmermann, Jesko; González, Ainhoa; Jones, Michael; O'Brien, Phillip; Stout, Jane C.; Green, Stuart

2016-04-01

In developed countries, cropland and grassland conversions and management can be a major factor in Land Use and Land Use Change (LULUC) related Greenhouse Gas (GHG) dynamics. Depending on land use, management and factors such as soil properties land can either act as source or sink for GHGs. Currently many countries depend on national statistics combined with socio-economic modelling to assess current land use as well as inter-annual changes. This potentially introduces a bias as it neither provides information on direct land- use change trajectories nor spatially explicit information to assess the environmental context. In order to improve reporting countries are shifting towards high resolution spatial datasets. In this case study, we used the Land Parcel Identification System (LPIS), a pan-European geographical database developed to assist farmers and authorities with agricultural subsidies, to analyse cropland dynamics in Ireland. The database offer high spatial resolution and is updated annually. Generally Ireland is considered grassland dominated with 90 % of its agricultural area under permanent grassland, and only a small area dedicated to cropland. However an in-depth analysis of the LPIS for the years 2000 to 2012 showed strong underlying dynamics. While the annual area reported as cropland remained relatively constant at 3752.3 ± 542.3 km2, the area of permanent cropland was only 1251.9 km2. Reversely, the area that was reported as cropland for at least one year during the timeframe was 7373.4 km2, revealing a significantly higher area with cropland history than annual statistics would suggest. Furthermore, the analysis showed that one quarter of the land converting from or to cropland will return to the previous land use within a year. To demonstrate potential policy impact, we assessed cropland/grassland dynamics from the 2008 to 2012 commitment period using (a) annual statistics, and (b) data including land use history derived from LPIS. Under current reporting standards temporary grassland is considered cropland for reporting purposes. Therefore taking land use history into account increases the area reported as cropland in 2008 by 45.7 % and the area remaining cropland in 2012 by 17.5 % compared to using annual statistics. In conclusion we showed that high resolution spatial datasets are an important tool to better understand land use dynamics, and can directly improve national GHG accounting efforts. Furthermore, knowledge of land use history is important to assess local GHG dynamics, and can therefore contribute to ultimately progress reporting to higher Tier level reporting.

Spatiotemporal dynamics of landscape pattern and hydrologic process in watershed systems

NASA Astrophysics Data System (ADS)

Randhir, Timothy O.; Tsvetkova, Olga

2011-06-01

SummaryLand use change is influenced by spatial and temporal factors that interact with watershed resources. Modeling these changes is critical to evaluate emerging land use patterns and to predict variation in water quantity and quality. The objective of this study is to model the nature and emergence of spatial patterns in land use and water resource impacts using a spatially explicit and dynamic landscape simulation. Temporal changes are predicted using a probabilistic Markovian process and spatial interaction through cellular automation. The MCMC (Monte Carlo Markov Chain) analysis with cellular automation is linked to hydrologic equations to simulate landscape patterns and processes. The spatiotemporal watershed dynamics (SWD) model is applied to a subwatershed in the Blackstone River watershed of Massachusetts to predict potential land use changes and expected runoff and sediment loading. Changes in watershed land use and water resources are evaluated over 100 years at a yearly time step. Results show high potential for rapid urbanization that could result in lowering of groundwater recharge and increased storm water peaks. The watershed faces potential decreases in agricultural and forest area that affect open space and pervious cover of the watershed system. Water quality deteriorated due to increased runoff which can also impact stream morphology. While overland erosion decreased, instream erosion increased from increased runoff from urban areas. Use of urban best management practices (BMPs) in sensitive locations, preventive strategies, and long-term conservation planning will be useful in sustaining the watershed system.

A numerical study of the effect of irrigation on land-atmosphere interactions in a spring wheat cropland in India using a coupled atmosphere-crop growth dynamics model

NASA Astrophysics Data System (ADS)

Kumari, S.; Sharma, P.; Srivastava, A.; Rastogi, D.; Sehgal, V. K.; Dhakar, R.; Roy, S. B.

2017-12-01

Vegetation dynamics and surface meteorology are tightly coupled through the exchange of momentum, moisture and heat between the land surface and the atmosphere. In this study, we use a recently developed coupled atmosphere-crop growth dynamics model to study these exchanges and their effects in a spring wheat cropland in northern India. In particular, we investigate the role of irrigation in controlling crop growth rates, surface meteorology, and sensible and latent heat fluxes. The model is developed by implementing a crop growth module based on the Simple and Universal Crop growth Simulator (SUCROS) model in the Weather Research Forecasting (WRF) mesoscale atmospheric model. The crop module calculates photosynthesis rates, carbon assimilation, and biomass partitioning as a function of environmental factors and crop development stage. The leaf area index (LAI) and root depth calculated by the crop module is then fed to the Noah-MP land module of WRF to calculate land-atmosphere fluxes. The crop model is calibrated using data from an experimental spring wheat crop site in the Indian Agriculture Research Institute. The coupled model is capable of simulating the observed spring wheat phenology. Irrigation is simulated by changing the soil moisture levels from 50% - 100% of field capacity. Results show that the yield first increases with increasing soil moisture and then starts decreasing as we further increase the soil moisture. Yield attains its maximum value with soil moisture at the level of 60% water of FC. At this level, high LAI values lead to a decrease in the Bowen Ratio because more energy is transferred to the atmosphere as latent heat rather than sensible heat resulting in a cooling effect on near-surface air temperatures. Apart from improving simulation of land-atmosphere interactions, this coupled modeling approach can form the basis for the seamless crop yield and seasonal scale weather outlook prediction system.

Climate simulation of the twenty-first century with interactive land-use changes

NASA Astrophysics Data System (ADS)

Voldoire, Aurore; Eickhout, Bas; Schaeffer, Michiel; Royer, Jean-François; Chauvin, Fabrice

2007-08-01

To include land-use dynamics in a general circulation model (GCM), the physical system has to be linked to a system that represents socio-economy. This issue is addressed by coupling an integrated assessment model, IMAGE2.2, to an ocean atmosphere GCM, CNRM-CM3. In the new system, IMAGE2.2 provides CNRM-CM3 with all the external forcings that are scenario dependent: greenhouse gas (GHGs) concentrations, sulfate aerosols charge and land cover. Conversely, the GCM gives IMAGE changes in mean temperature and precipitation. With this new system, we have run an adapted scenario of the IPCC SRES scenario family. We have chosen a single scenario with maximum land-use changes (SRES A2), to illustrate some important feedback issues. Even in this two-way coupled model set-up, land use in this scenario is mainly driven by demographic and agricultural practices, which overpowers a potential influence of climate feedbacks on land-use patterns. This suggests that for scenarios in which socio-economically driven land-use change is very large, land-use changes can be incorporated in GCM simulations as a one-way driving force, without taking into account climate feedbacks. The dynamics of natural vegetation is more closely linked to climate but the time-scale of changes is of the order of a century. Thus, the coupling between natural vegetation and climate could generate important feedbacks but these effects are relevant mainly for multi-centennial simulations.

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE)

PubMed Central

Tian, Xin; Li, Zengyuan; Chen, Erxue; Liu, Qinhuo; Yan, Guangjian; Wang, Jindi; Niu, Zheng; Zhao, Shaojie; Li, Xin; Pang, Yong; Su, Zhongbo; van der Tol, Christiaan; Liu, Qingwang; Wu, Chaoyang; Xiao, Qing; Yang, Le; Mu, Xihan; Bo, Yanchen; Qu, Yonghua; Zhou, Hongmin; Gao, Shuai; Chai, Linna; Huang, Huaguo; Fan, Wenjie; Li, Shihua; Bai, Junhua; Jiang, Lingmei; Zhou, Ji

2015-01-01

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE) comprises a network of remote sensing experiments designed to enhance the dynamic analysis and modeling of remotely sensed information for complex land surfaces. Two types of experimental campaigns were established under the framework of COMPLICATE. The first was designed for continuous and elaborate experiments. The experimental strategy helps enhance our understanding of the radiative and scattering mechanisms of soil and vegetation and modeling of remotely sensed information for complex land surfaces. To validate the methodologies and models for dynamic analyses of remote sensing for complex land surfaces, the second campaign consisted of simultaneous satellite-borne, airborne, and ground-based experiments. During field campaigns, several continuous and intensive observations were obtained. Measurements were undertaken to answer key scientific issues, as follows: 1) Determine the characteristics of spatial heterogeneity and the radiative and scattering mechanisms of remote sensing on complex land surfaces. 2) Determine the mechanisms of spatial and temporal scale extensions for remote sensing on complex land surfaces. 3) Determine synergist inversion mechanisms for soil and vegetation parameters using multi-mode remote sensing on complex land surfaces. Here, we introduce the background, the objectives, the experimental designs, the observations and measurements, and the overall advances of COMPLICATE. As a result of the implementation of COMLICATE and for the next several years, we expect to contribute to quantitative remote sensing science and Earth observation techniques. PMID:26332035

Mapping, monitoring, and modeling Western Gateway Community landscape dynamics

USGS Publications Warehouse

Hester, David J.

2013-01-01

Federal public lands in the western United States are becoming increasingly surrounded by Gateway Communities. These communities are undergoing landscape change due to population growth, economic growth, and the resulting land-use development. Socioeconomic, demographic, and land-use changes in Gateway Communities are often perceived as threats to Federal land resources, natural amenities, cultural resources, and recreational opportunities. However, land-surface disturbances on Federal public lands, such as conventional and alternative energy development (which impact surrounding Gateway Communities), are also environmental and societal issues that Federal land and adjacent regional community planners need to consider in their long-range land-use planning.

Effects of harvest on carbon and nitrogen dynamics in a Pacific Northwest forest catchment

EPA Science Inventory

We used a new ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA), to analyze the effects of forest harvest on catchment carbon and nitrogen dynamics. We applied the model to a 10 ha headwater catchment in the western Oregon Cascade Range where t...

The Value of GRACE Data in Improving, Assessing and Evaluating Land Surface and Climate Models

NASA Astrophysics Data System (ADS)

Yang, Z.

2011-12-01

I will review how the Gravity Recovery and Climate Experiment (GRACE) satellite measurements have improved land surface models that are developed for weather, climate, and hydrological studies. GRACE-derived terrestrial water storage (TWS) changes have been successfully used to assess and evaluate the improved representations of land-surface hydrological processes such as groundwater-soil moisture interaction, frozen soil and infiltration, and the topographic control on runoff production, as evident in the simulations from the latest Noah-MP, the Community Land Model, and the Community Climate System Model. GRACE data sets have made it possible to estimate key terrestrial water storage components (snow mass, surface water, groundwater or water table depth), biomass, and surface water fluxes (evapotranspiration, solid precipitation, melt of snow/ice). Many of the examples will draw from my Land, Environment and Atmosphere Dynamics group's work on land surface model developments, snow mass retrieval, and multi-sensor snow data assimilation using the ensemble Karman filter and the ensemble Karman smoother. Finally, I will briefly outline some future directions in using GRACE in land surface modeling.

Modeling the dynamics of urban growth using multinomial logistic regression: a case study of Jiayu County, Hubei Province, China

NASA Astrophysics Data System (ADS)

Nong, Yu; Du, Qingyun; Wang, Kun; Miao, Lei; Zhang, Weiwei

2008-10-01

Urban growth modeling, one of the most important aspects of land use and land cover change study, has attracted substantial attention because it helps to comprehend the mechanisms of land use change thus helps relevant policies made. This study applied multinomial logistic regression to model urban growth in the Jiayu county of Hubei province, China to discover the relationship between urban growth and the driving forces of which biophysical and social-economic factors are selected as independent variables. This type of regression is similar to binary logistic regression, but it is more general because the dependent variable is not restricted to two categories, as those previous studies did. The multinomial one can simulate the process of multiple land use competition between urban land, bare land, cultivated land and orchard land. Taking the land use type of Urban as reference category, parameters could be estimated with odds ratio. A probability map is generated from the model to predict where urban growth will occur as a result of the computation.

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.

76 FR 291 - Special Conditions: Gulfstream Model GVI Airplane; Single-Occupant Side-Facing Seats

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-04

...-occupant side-facing seat installations. Dynamic testing of all seats approved for occupancy during takeoff.... 25.562, ``Emergency landing dynamic conditions,'' requires dynamic testing of all seats occupied... seats, or seats equipped with conventional restraint systems. [[Page 292

Model estimation of land-use effects on water levels of northern Prairie wetlands

USGS Publications Warehouse

Voldseth, R.A.; Johnson, W.C.; Gilmanov, T.; Guntenspergen, G.R.; Millett, B.V.

2007-01-01

Wetlands of the Prairie Pothole Region exist in a matrix of grassland dominated by intensive pastoral and cultivation agriculture. Recent conservation management has emphasized the conversion of cultivated farmland and degraded pastures to intact grassland to improve upland nesting habitat. The consequences of changes in land-use cover that alter watershed processes have not been evaluated relative to their effect on the water budgets and vegetation dynamics of associated wetlands. We simulated the effect of upland agricultural practices on the water budget and vegetation of a semipermanent prairie wetland by modifying a previously published mathematical model (WETSIM). Watershed cover/land-use practices were categorized as unmanaged grassland (native grass, smooth brome), managed grassland (moderately heavily grazed, prescribed burned), cultivated crops (row crop, small grain), and alfalfa hayland. Model simulations showed that differing rates of evapotranspiration and runoff associated with different upland plant-cover categories in the surrounding catchment produced differences in wetland water budgets and linked ecological dynamics. Wetland water levels were highest and vegetation the most dynamic under the managed-grassland simulations, while water levels were the lowest and vegetation the least dynamic under the unmanaged-grassland simulations. The modeling results suggest that unmanaged grassland, often planted for waterfowl nesting, may produce the least favorable wetland conditions for birds, especially in drier regions of the Prairie Pothole Region. These results stand as hypotheses that urgently need to be verified with empirical data.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Model studies of crosswind landing-gear configurations for STOL aircraft

NASA Technical Reports Server (NTRS)

Stubbs, S. M.; Byrdsong, T. A.

1973-01-01

A dynamic model was used to directly compare four different crosswind landing gear mechanisms. The model was landed as a free body onto a laterally sloping runway used to simulate a crosswind side force. A radio control system was used for steering to oppose the side force as the model rolled to a stop. The configuration in which the landing gears are alined by the pilot and locked in the direction of motion prior to touchdown gave the smoothest runout behavior with the vehicle maintaining its crab angle throughout the landing roll. Nose wheel steering was confirmed to be better than steering with nose and main gears differentially or together. Testing is continuing to obtain quantitative data to establish an experimental data base for validation of an analytical program that will be capable of predicting full scale results.

Integrating SPOT-VEGETATION 13-yr time series and land-surface modelling to forecast the terrestrial carbon dynamics in a changing climate - The VEGECLIM project: achievements and lessons learned

NASA Astrophysics Data System (ADS)

Defourny, Pierre; Verbeeck, Hans; Moreau, Inès; De Weirdt, Marjolein; Verhegghen, Astrid; Kibambe-Lubamba, Jean-Paul; Jungers, Quentin; Maignan, Fabienne; Najdovski, Nicolas; Poulter, Benjamin; MacBean, Natasha; Peylin, Philippe

2014-05-01

Vegetation is a major carbon sink and is as such a key component of the international response to climate change caused by the build-up of greenhouse gases in the atmosphere. However, anthropogenic disturbances like deforestation are the primary mechanism that changes ecosystems from carbon sinks to sources, and are hardly included in the current carbon modelling approaches. Moreover, in tropical regions, the seasonal/interannual variability of carbon fluxes is still uncertain and a weak or even no seasonality is taken into account in global vegetation models. In the context of climate change and mitigation policies like "Reducing Emissions from Deforestation and Forest Degradation in Developing Countries" (REDD), it is particularly important to be able to quantify and forecast the vegetation dynamics and carbon fluxes in these regions. The overall objective of the VEGECLIM project is to increase our knowledge on the terrestrial carbon cycle in tropical regions and to improve the forecast of the vegetation dynamics and carbon stocks and fluxes under different climate-change and deforestation scenarios. Such an approach aims to determine whether the African terrestrial carbon balance will remain a net sink or could become a carbon source by the end of the century, according to different climate-change and deforestation scenarios. The research strategy is to integrate the information of the land surface characterizations obtained from 13 years of consistent SPOT-VEGETATION time series (land cover, vegetation phenology through vegetation indices such as the Enhanced Vegetation Index (EVI)) as well as in-situ carbon flux data into the process based ORCHIDEE global vegetation model, capable of simulating vegetation dynamics and carbon balance. Key challenge of this project was to bridge the gap between the land cover and the land surface model teams. Several improvements of the ORCHIDEE model have been realized such as a new seasonal leaf dynamics for tropical evergreen forests, the introduction of spatial soil phosphorus to improve the spatial distribution of simulated woody biomass and an assimilation of smoothed seasonal pattern of satellite-based EVI used as a proxy to vegetation productivity. The outputs of the ORCHIDEE simulations over both Amazon and Congo Basins are discussed with regards to the observed phenology by remote sensing.

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

NASA Astrophysics Data System (ADS)

Slater, L. J.; Villarini, G.

2017-12-01

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

Computing Dynamics Of A Robot Of 6+n Degrees Of Freedom

NASA Technical Reports Server (NTRS)

Quiocho, Leslie J.; Bailey, Robert W.

1995-01-01

Improved formulation speeds and simplifies computation of dynamics of robot arm of n rotational degrees of freedom mounted on platform having three translational and three rotational degrees of freedom. Intended for use in dynamical modeling of robotic manipulators attached to such moving bases as spacecraft, aircraft, vessel, or land vehicle. Such modeling important part of simulation and control of robotic motions.

Importance of soil thermal dynamics on land carbon sequestration in Northern Eurasia during the 21st century

NASA Astrophysics Data System (ADS)

Kicklighter, David; Monier, Erwan; Sokolov, Andrei; Zhuang, Qianlai; Melillo, Jerry

2015-04-01

Recent modeling studies have suggested that carbon sinks in pan-arctic ecosystems may be weakening partially as a result of warming-induced increases in soil organic matter (SOM) decomposition and the exposure of previously frozen SOM to decomposition. This weakening of carbon sinks is likely to continue in the future as vast amount of carbon in permafrost soils is vulnerable to thaw. Here, we examine the importance of considering soil thermal dynamics when determining the effects of climate change and land-use change on carbon dynamics in Northern Eurasia during the 21st century. This importance is assessed by comparing results for a "business as usual" scenario between a version of the Terrestrial Ecosystem Model that does not consider soil thermal dynamics (TEM 4.4) and a version that does consider these dynamics (TEM 6.0). In this scenario, which is similar to the IPCC Representative Concentration Pathways (RCP) 8.5 scenario, the net area covered by food crops and pastures in Northern Eurasia is assumed to remain relatively constant over the 21st century, but the area covered by secondary forests is projected to double as a result of timber harvest and the abandonment of land associated with displacement of agricultural land. Enhanced decomposition from the newly exposed SOM from permafrost thaw also increases nitrogen availability for plant production so that the loss of carbon from the enhanced decomposition is partially compensated by enhanced uptake and storage of atmospheric carbon dioxide in vegetation. Our results indicate that consideration of soil thermal dynamics have a large influence on how simulated terrestrial carbon dynamics in Northern Eurasia respond to changes in climate, atmospheric chemistry (e.g., carbon dioxide fertilization, ozone pollution, nitrogen deposition) and disturbances.

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.

APPLICATION OF LAND-COVER DATA FOR ENVIRONMENTAL ASSESSMENTS

EPA Science Inventory

In many parts of the United States, urbanization is a pervasive dynamic that has many environmental consequences. Land-cover and related (e.g. Landsat) data are fundamental for studying urbanization itself and its environmental effects.

Well established models in economic...

Simulating the dynamics of linear forests in great plains agroecosystems under changing climates

Treesearch

Qinfeng Guo; J. Brandle; Michele Schoeneberger; D. Buettner

2004-01-01

Most forest growth models are not suitable for the highly fragmented, linear (or linearly shaped) forests in the Great Plains agroecosystems (e.g., windbreaks, riparian forest buffers), where such forests are a minor but ecologically important component of the land mosaics. This study used SEEI)SCAPE, a recently modified gap model designed for cultivated land mosaics...

Contributions of secondary forest and nitrogen dynamics to terrestrial carbon uptake

NASA Astrophysics Data System (ADS)

Yang, X.; Richardson, T. K.; Jain, A. K.

2010-10-01

We use a terrestrial carbon-nitrogen cycle component of the Integrated Science Assessment Model (ISAM) to investigate the impacts of nitrogen dynamics on regrowing secondary forests over the 20th century. We further examine what the impacts of nitrogen deposition and land use change history are on terrestrial carbon uptake since preindustrial time. Our results suggest that global total net land use emissions for the 1990s associated with changes in cropland, pastureland, and wood harvest are 1.22 GtC/yr. Without considering the secondary forest regrowth, the estimated net global total land use emissions are 1.58 GtC/yr or about 0.36 GtC/yr higher than if secondary forest regrowth is considered. Results also show that without considering the nitrogen dynamics and deposition, the estimated global total secondary forest sink for the 1990s is 0.90 GtC/yr or about 0.54 GtC/yr higher than estimates that include the impacts of nitrogen dynamics and deposition. Nitrogen deposition alone is responsible for about 0.13 GtC/yr of the total secondary forest sink. While nitrogen is not a limiting nutrient in the intact primary forests in tropical regions, our study suggests that nitrogen becomes a limiting nutrient for regrowing secondary forests of the tropical regions, in particular Latin America and Tropical Africa. This is because land use change activities, especially wood harvest, removes large amounts of nitrogen from the system when slash is burnt or wood is removed for harvest. However, our model results show that carbon uptake is enhanced in the tropical secondary forests of the Indian region. We argue that this may be due to enhanced nitrogen mineralization and increased nitrogen availability following land use change in the Indian tropical forest ecosystems. Results also demonstrate that there is a significant amount of carbon accumulating in the Northern Hemisphere where most land use changes and forest regrowth has occurred in recent decades. This study indicates the significance of secondary forests to terrestrial carbon sinks, the importance of nitrogen dynamics to the magnitude of secondary forests carbon uptake, and therefore the need to include both primary and secondary forests and nitrogen dynamics in terrestrial ecosystem models.

Contributions of secondary forest and nitrogen dynamics to terrestrial carbon uptake

NASA Astrophysics Data System (ADS)

Yang, X.; Richardson, T. K.; Jain, A. K.

2010-04-01

We use a terrestrial carbon-nitrogen cycle component of the Integrated Science Assessment Model (ISAM) to investigate the impacts of nitrogen dynamics on regrowing secondary forests over the 20th century. We further examine what the impacts of nitrogen deposition and land use change history are on terrestrial carbon uptake since preindustrial time. Our results suggest that global total net land use emissions for the 1990s associated with changes in cropland, pastureland, and wood harvest are 1.22 GtC/yr. Without considering the secondary forest regrowth, the estimated net global total land use emissions are 1.58 GtC/yr or about 0.36 GtC/yr higher than if secondary forest regrowth is considered. Results also show that without considering the nitrogen dynamics and deposition, the estimated global total secondary forest sink for the 1990s is 0.90 GtC/yr or about 0.54 GtC/yr higher than estimates that include the impacts of nitrogen dynamics and deposition. Nitrogen deposition alone is responsible for about 0.13 GtC/yr of the total secondary forest sink. While nitrogen is not a limiting nutrient in the intact primary forests in tropical regions, our study suggests that nitrogen becomes a limiting nutrient for regrowing secondary forests of the tropical regions, in particular Latin America and Tropical Africa. This is because land use change activities, especially wood harvest, removes large amounts of nitrogen from the system when slash is burnt or wood is removed for harvest. However, our model results show that carbon uptake is enhanced in the tropical secondary forests of the Indian region. We argue that this may be due to enhanced nitrogen mineralization and increased nitrogen availability following land use change in the Indian tropical forest ecosystems. Results also demonstrate that there is a significant amount of carbon accumulating in the Northern Hemisphere where most land use changes and forest regrowth has occurred in recent decades. This study indicates the significance of secondary forests to terrestrial carbon sinks, the importance of nitrogen dynamics to the magnitude of secondary forests carbon uptake, and therefore the need to include both primary and secondary forests and nitrogen dynamics in terrestrial ecosystem models.

Simulating Vibrations in a Complex Loaded Structure

NASA Technical Reports Server (NTRS)

Cao, Tim T.

2005-01-01

The Dynamic Response Computation (DIRECT) computer program simulates vibrations induced in a complex structure by applied dynamic loads. Developed to enable rapid analysis of launch- and landing- induced vibrations and stresses in a space shuttle, DIRECT also can be used to analyze dynamic responses of other structures - for example, the response of a building to an earthquake, or the response of an oil-drilling platform and attached tanks to large ocean waves. For a space-shuttle simulation, the required input to DIRECT includes mathematical models of the space shuttle and its payloads, and a set of forcing functions that simulates launch and landing loads. DIRECT can accommodate multiple levels of payload attachment and substructure as well as nonlinear dynamic responses of structural interfaces. DIRECT combines the shuttle and payload models into a single structural model, to which the forcing functions are then applied. The resulting equations of motion are reduced to an optimum set and decoupled into a unique format for simulating dynamics. During the simulation, maximum vibrations, loads, and stresses are monitored and recorded for subsequent analysis to identify structural deficiencies in the shuttle and/or payloads.

Computational fluid dynamic (CFD) analysis on ALUDRA SR-10 UAV with parachute recovery system

NASA Astrophysics Data System (ADS)

Saim, R.; Mohd, S.; Shamsudin, S. S.; Zulkifli, M. F.; Omar, Z.; Subari@Rahmat, Z.; Masrom, M. F. Mohd; Zaki, Y.

2017-09-01

In an operation, belly landing is mostly applied as recovery method especially on research Unmanned Aerial Vehicle (UAV) such as Aludra SR-10. This type of landing method may encounter tough landing on hard soil and gravel which create high impact load on the aircraft. The impact may cause structural or system damage which costly to be repaired. Nowadays, Parachute Recovery System (PRS) recently used in numerous different tasks such as landing purpose to replace belly landing technique. Parachute use in this system to slow down flying or falling UAV to a safe landing by opening the canopy to increase aerodynamic drag. This paper was described the Computational Fluid Dynamic (CFD) analysis on ALUDRA SR-10 model with two different conditions i.e. the UAV equipped with and without parachute in order to identify the changes of aerodynamic characteristics. This simulation studies using solid models of aircraft and hemisphere parachute and was carried out by using ANSYS 16.0 Fluent under steady and turbulent flow and was modelled using the k-epsilon (k-ε) turbulence model. This simulation was limited to determine the drag force and drag coefficient. The obtained result showed that implementation of parachute increase 0.25 drag coefficient of the aircraft that is from 0.93 to 1.18. Subsequent to the reduction of descent rate caused by the parachute, the drag force of the aircraft increase by 0.76N. These increasing of drag force of the aircraft will produce lower terminal velocity which is expected to reduce the impact force on the aircraft during landing.

An experimental simulation study of four crosswind landing gear concepts

NASA Technical Reports Server (NTRS)

Stubbs, S. M.; Byrdsong, T. A.; Sleeper, R. K.

1975-01-01

An experimental investigation was conducted in order to evaluate several crosswind landing-gear concepts which have a potential application to tricycle-gear-configured, short take-off and landing (STOL) aircraft landing at crab or heading angles up to 30 deg. In this investigation, the landing gears were installed on a dynamic model which had a scaled mass distribution and gear spacing but no aerodynamic similarities when compared with a typical STOL aircraft. The model was operated as a free body with radio-control steering and was launched onto a runway sloped laterally in order to provide a simulated crosswind side force. During the landing rollout, the gear forces and the model trajectory were measured and the various concepts were compared with each other. Within the test limitations, the landing gear system, in which the gears were alined by the pilot and locked in the direction of motion prior to touchdown, gave the smoothest runout behavior with the vehicle maintaining its crab angle throughout the landing runout.

A multi-model framework for simulating wildlife population response to land-use and climate change

USGS Publications Warehouse

McRae, B.H.; Schumaker, N.H.; McKane, R.B.; Busing, R.T.; Solomon, A.M.; Burdick, C.A.

2008-01-01

Reliable assessments of how human activities will affect wildlife populations are essential for making scientifically defensible resource management decisions. A principle challenge of predicting effects of proposed management, development, or conservation actions is the need to incorporate multiple biotic and abiotic factors, including land-use and climate change, that interact to affect wildlife habitat and populations through time. Here we demonstrate how models of land-use, climate change, and other dynamic factors can be integrated into a coherent framework for predicting wildlife population trends. Our framework starts with land-use and climate change models developed for a region of interest. Vegetation changes through time under alternative future scenarios are predicted using an individual-based plant community model. These predictions are combined with spatially explicit animal habitat models to map changes in the distribution and quality of wildlife habitat expected under the various scenarios. Animal population responses to habitat changes and other factors are then projected using a flexible, individual-based animal population model. As an example application, we simulated animal population trends under three future land-use scenarios and four climate change scenarios in the Cascade Range of western Oregon. We chose two birds with contrasting habitat preferences for our simulations: winter wrens (Troglodytes troglodytes), which are most abundant in mature conifer forests, and song sparrows (Melospiza melodia), which prefer more open, shrubby habitats. We used climate and land-use predictions from previously published studies, as well as previously published predictions of vegetation responses using FORCLIM, an individual-based forest dynamics simulator. Vegetation predictions were integrated with other factors in PATCH, a spatially explicit, individual-based animal population simulator. Through incorporating effects of landscape history and limited dispersal, our framework predicted population changes that typically exceeded those expected based on changes in mean habitat suitability alone. Although land-use had greater impacts on habitat quality than did climate change in our simulations, we found that small changes in vital rates resulting from climate change or other stressors can have large consequences for population trajectories. The ability to integrate bottom-up demographic processes like these with top-down constraints imposed by climate and land-use in a dynamic modeling environment is a key advantage of our approach. The resulting framework should allow researchers to synthesize existing empirical evidence, and to explore complex interactions that are difficult or impossible to capture through piecemeal modeling approaches. ?? 2008 Elsevier B.V.

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.

A Prototype Physical Database for Passive Microwave Retrievals of Precipitation over the US Southern Great Plains

NASA Technical Reports Server (NTRS)

Ringerud, S.; Kummerow, C. D.; Peters-Lidard, C. D.

2015-01-01

An accurate understanding of the instantaneous, dynamic land surface emissivity is necessary for a physically based, multi-channel passive microwave precipitation retrieval scheme over land. In an effort to assess the feasibility of the physical approach for land surfaces, a semi-empirical emissivity model is applied for calculation of the surface component in a test area of the US Southern Great Plains. A physical emissivity model, using land surface model data as input, is used to calculate emissivity at the 10GHz frequency, combining contributions from the underlying soil and vegetation layers, including the dielectric and roughness effects of each medium. An empirical technique is then applied, based upon a robust set of observed channel covariances, extending the emissivity calculations to all channels. For calculation of the hydrometeor contribution, reflectivity profiles from the Tropical Rainfall Measurement Mission Precipitation Radar (TRMM PR) are utilized along with coincident brightness temperatures (Tbs) from the TRMM Microwave Imager (TMI), and cloud-resolving model profiles. Ice profiles are modified to be consistent with the higher frequency microwave Tbs. Resulting modeled top of the atmosphere Tbs show correlations to observations of 0.9, biases of 1K or less, root-mean-square errors on the order of 5K, and improved agreement over the use of climatological emissivity values. The synthesis of these models and data sets leads to the creation of a simple prototype Tb database that includes both dynamic surface and atmospheric information physically consistent with the land surface model, emissivity model, and atmospheric information.

What hydrological dynamics emerge from the interaction of land conversion and flood levee construction? Using dynamical systems models to explore the development of California's Sacramento-San Joaquin Watersheds.

NASA Astrophysics Data System (ADS)

Thompson, S. E.; Hutton, P.; Sivapalan, M.; MacVean, L. J.

2016-12-01

The hydrological impacts of land development include the simultaneous modifications of land cover, water abstraction and hydraulics. While reservoir construction and irrigation offer water managers de facto control of the hydrologic budget in the upper and middle reaches of river basins, the pattern of development in lowland areas incorporates drainage of wetlands, leveeing of flood plains, and rain-fed agriculture. The resulting hydrological function is then an emergent property of the interaction of land use change with flood control infrastructure. Using the lowland areas of California's Sacramento and San Joaquin Rivers as a motivating case study, we showed that this emergent behavior arises from two key interacting stochastic processes: one governing the water available to and used by dryland agriculture, and one governing the spatial dynamics of near-channel flooding impounded by levees. Comparable annual water balance dynamics can arise under managed and unmanaged conditions. Similarities in water balance, however, can mask large differences in seasonality and channel hydraulics.

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.

Catchment hydro-biogeochemical response to climate change and future land-use

EPA Science Inventory

The potential interacting effects of climate change and future land-use on hydrological and biogeochemical dynamics rarely have been described at the catchment level and are difficult or impossible to capture through experimentation or observation alone. We apply a new model, Vi...

Dynamic simulation and numerical analysis of hurricane storm surge under sea level rise with geomorphologic changes along the northern Gulf of Mexico

USGS Publications Warehouse

Bilskie, Matthew V.; Hagen, S.C.; Alizad, K.A.; Medeiros, S.C.; Passeri, Davina L.; Needham, H.F.; Cox, A.

2016-01-01

This work outlines a dynamic modeling framework to examine the effects of global climate change, and sea level rise (SLR) in particular, on tropical cyclone-driven storm surge inundation. The methodology, applied across the northern Gulf of Mexico, adapts a present day large-domain, high resolution, tide, wind-wave, and hurricane storm surge model to characterize the potential outlook of the coastal landscape under four SLR scenarios for the year 2100. The modifications include shoreline and barrier island morphology, marsh migration, and land use land cover change. Hydrodynamics of 10 historic hurricanes were simulated through each of the five model configurations (present day and four SLR scenarios). Under SLR, the total inundated land area increased by 87% and developed and agricultural lands by 138% and 189%, respectively. Peak surge increased by as much as 1 m above the applied SLR in some areas, and other regions were subject to a reduction in peak surge, with respect to the applied SLR, indicating a nonlinear response. Analysis of time-series water surface elevation suggests the interaction between SLR and storm surge is nonlinear in time; SLR increased the time of inundation and caused an earlier arrival of the peak surge, which cannot be addressed using a static (“bathtub”) modeling framework. This work supports the paradigm shift to using a dynamic modeling framework to examine the effects of global climate change on coastal inundation. The outcomes have broad implications and ultimately support a better holistic understanding of the coastal system and aid restoration and long-term coastal sustainability.

Importance of Nitrogen Availability on Land Carbon Sequestration in Northern Eurasia during the 21st Century

NASA Astrophysics Data System (ADS)

Kicklighter, D. W.; Melillo, J. M.; Monier, E.; Sokolov, A. P.; Lu, X.; Zhuang, Q.

2015-12-01

Atmospheric nitrogen deposition, nitrogen fixation, and the application of nitrogen fertilizers provide subsidies to land ecosystems that can increase nitrogen availability for vegetation production and thereby influence land carbon dynamics. In addition, enhanced decomposition of soil organic matter (SOM) from warming soils and permafrost degradation may also increase nitrogen availability in Northern Eurasia. Here, we examine how changes in nitrogen availability may influence land carbon dynamics in Northern Eurasia during the 21st century by comparing results for a "business as usual" scenario (the IPCC Representative Concentration Pathways or RCP 8.5) and a stabilization scenario (RCP 4.5) between a version of the Terrestrial Ecosystem Model that does not consider the effects of atmospheric nitrogen deposition, nitrogen fixation and soil thermal dynamics on land carbon dynamics (TEM 4.4) and a version that does consider these dynamics (TEM 6.0). In these simulations, atmospheric nitrogen deposition, nitrogen fixation, and fertilizer applications provide an additional 3.3 Pg N (RCP 4.5) to 3.9 Pg N (RCP 8.5) to Northern Eurasian ecosystems over the 21st century. Land ecosystems retain about 38% (RCP4.5) to 48% (RCP 8.5) of this nitrogen subsidy. Net nitrogen mineralization estimated by TEM 6.0 provide an additional 1.0 Pg N to vegetation than estimated by TEM 4.4 over the 21st century from enhanced decomposition of SOM including SOM formerly protected by permafrost. The enhanced nitrogen availability in TEM 6.0 allows Northern Eurasian ecosystems to sequester 1.8x (RCP 8.5) to 2.4x (RCP 4.5) more carbon over the 21st century than estimated by TEM 4.4. Our results indicate that consideration of nitrogen subsidies and soil thermal dynamics have a large influence on how simulated land carbon dynamics in Northern Eurasia will respond to future changes in climate, atmospheric chemistry, and disturbances.

Mapping Process to Pattern in the Landscape Change of the Amazonian Frontier

NASA Technical Reports Server (NTRS)

Walker, Robert

2003-01-01

Changes in land use and land cover are dynamic processes reflecting a sequence of decisions made by individual land managers. In developing economies, these decisions may be embedded in the evolution of individual households, as is often the case in indigenous areas and agricultural frontiers. One goal of the present article is to address the land use and land-cover decisions of colonist farmers in the Amazon Basin as a function, in part, of household characteristics. Another goal is to generalize the issue of tropical deforestation into a broader discussion on forest dynamics. The extent of secondary forest in tropical areas has been well documented in South America and Africa. Agricultural-plot abandonment often occurs in tandem with primary forest clearance and as part of the same decision-making calculus. Consequently, tropical deforestation and forest succession are not independent processes in the landscape. This article presents a framework that integrates them into a model of forest dynamics at household level, and in so doing provides an account of the spatial pattern of deforestation that has been observed in the Amazon's colonization frontiers.

Modeling the effect of terraces on land degradation in tropical upland agricultural area

NASA Astrophysics Data System (ADS)

Christanto, N.; Shrestha, D. P.; Jetten, V. G.; Setiawan, A.

2012-04-01

Java, the most populated Island in Indonesia, in the pas view decades suffer land degradation do to extreme weather, population pressure and landuse/cover change. The study area, Serayu sub-catchment, as part of Serayu catchment is one of the representative example of Indonesia region facing land use change and land degradation problem. The study attempted to simulate the effect of terraces on land degradation (Soil erosion and landslide hazard) in Serayu sub-catchment using deterministic modeling by means of PCRaster® simulation. The effect of the terraces on tropical upland agricultural area is less studied. This paper will discuss about the effect of terraces on land degradation assessment. Detail Dem is extremely difficult to obtain in developing country like Indonesia. Therefore, an artificial DEM which give an impression of the terraces was built. Topographical maps, Ikonos Image and average of height distribution based on field measurement were used to build the artificial DEM. The result is used in STARWARS model as an input. In combine with Erosion model and PROBSTAB, soil erosion and landslide hazard were quantified. The models were run in two different environment based on the: 1) normal DEM 2.) Artificial DEM (with terraces impression). The result is compared. The result shows that the models run in an artificial DEM give a significant increase on the probability of failure by 20.5%. In the other hand, the erosion rate has fall by 11.32% as compared to the normal DEM. The result of hydrological sensitivity analysis shows that soil depth was the most sensitive parameter. For the slope stability modeling, the most sensitive parameter was slope followed by friction angle and cohesion. The erosion modeling, the model was sensitive to the vegetation cover, soil erodibility followed by BD and KSat. Model validations were applied to assess the accuracy of the models. However, the results of dynamic modeling are ideal for land degradation assessment. Dynamic modeling software such as PC Raster® which is open source and free are reliable alternative to other commercial software

Dynamics of global vegetation biomass simulated by the integrated Earth System Model

NASA Astrophysics Data System (ADS)

Mao, J.; Shi, X.; Di Vittorio, A. V.; Thornton, P. E.; Piao, S.; Yang, X.; Truesdale, J. E.; Bond-Lamberty, B. P.; Chini, L. P.; Thomson, A. M.; Hurtt, G. C.; Collins, W.; Edmonds, J.

2014-12-01

The global vegetation biomass stores huge amounts of carbon and is thus important to the global carbon budget (Pan et al., 2010). For the past few decades, different observation-based estimates and modeling of biomass in the above- and below-ground vegetation compartments have been comprehensively conducted (Saatchi et al., 2011; Baccini et al., 2012). However, uncertainties still exist, in particular for the simulation of biomass magnitude, tendency, and the response of biomass to climatic conditions and natural and human disturbances. The recently successful coupling of the integrated Earth System Model (iESM) (Di Vittorio et al., 2014; Bond-Lamberty et al., 2014), which links the Global Change Assessment Model (GCAM), Global Land-use Model (GLM), and Community Earth System Model (CESM), offers a great opportunity to understand the biomass-related dynamics in a fully-coupled natural and human modeling system. In this study, we focus on the systematic analysis and evaluation of the iESM simulated historical (1850-2005) and future (2006-2100) biomass changes and the response of the biomass dynamics to various impact factors, in particular the human-induced Land Use/Land Cover Change (LULCC). By analyzing the iESM simulations with and without the interactive LULCC feedbacks, we further study how and where the climate feedbacks affect socioeconomic decisions and LULCC, such as to alter vegetation carbon storage. References Pan Y et. al: A large and persistent carbon sink in the World's forests. Science 2011, 333:988-993. Saatchi SS et al: Benchmark map of forest carbon stocks in tropical regions across three continents. Proc Natl Acad Sci 2011, 108:9899-9904. Baccini A et al: Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Clim Change 2012, 2:182-185. Di Vittorio AV et al: From land use to land cover: restoring the afforestation signal in a coupled integrated assessment-earth system model and the implications for CMIP5 RCP simulations. Biogeosciences Discuss 2014, 11:7151-7188. Bond-Lamberty, B et al: Coupling earth system and integrated assessment models: The problem of steady state. Geosci. Model Dev. Discuss 2014, 7: 1499-1524, doi:10.5194/gmdd-7-1499-2014.

The influence of agroforestry and other land-use types on the persistence of a Sumatran tiger (Panthera tigris sumatrae) population: an individual-based model approach.

PubMed

Imron, Muhammad Ali; Herzog, Sven; Berger, Uta

2011-08-01

The importance of preserving both protected areas and their surrounding landscapes as one of the major conservation strategies for tigers has received attention over recent decades. However, the mechanism of how land-use surrounding protected areas affects the dynamics of tiger populations is poorly understood. We developed Panthera Population Persistence (PPP)--an individual-based model--to investigate the potential mechanism of the Sumatran tiger population dynamics in a protected area and under different land-use scenarios surrounding the reserve. We tested three main landscape compositions (single, combined and real land-uses of Tesso-Nilo National Park and its surrounding area) on the probability of and time to extinction of the Sumatran tiger over 20 years in Central Sumatra. The model successfully explains the mechanisms behind the population response of tigers under different habitat landscape compositions. Feeding and mating behaviours of tigers are key factors, which determined population persistence in a heterogeneous landscape. All single land-use scenarios resulted in tiger extinction but had a different probability of extinction within 20 years. If tropical forest was combined with other land-use types, the probability of extinction was smaller. The presence of agroforesty and logging concessions adjacent to protected areas encouraged the survival of tiger populations. However, with the real land-use scenario of Tesso-Nilo National Park, tigers could not survive for more than 10 years. Promoting the practice of agroforestry systems surrounding the park is probably the most reasonable way to steer land-use surrounding the Tesso-Nilo National Park to support tiger conservation.

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

DOE PAGES

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.; ...

2016-10-20

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

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

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

PubMed Central

Sippel, Sebastian; Mahecha, Miguel D.; Hauhs, Michael; Bodesheim, Paul; Kaminski, Thomas; Gans, Fabian; Rosso, Osvaldo A.

2016-01-01

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics. PMID:27764187

Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images

NASA Astrophysics Data System (ADS)

He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun

2015-06-01

Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.

Uncertainty assessment of future land use in Brazil under increasing demand for bioenergy

NASA Astrophysics Data System (ADS)

van der Hilst, F.; Verstegen, J. A.; Karssenberg, D.; Faaij, A.

2013-12-01

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 spatio-temporal 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, three 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) a model to project the quantity of change of all land uses, and 3) a spatially explicit land use model that determines the location of change of all land uses. All three 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 2011 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 locations of pastures are uncertain. Since the 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. Results of the data assimilation indicate that the drivers of location of the land uses vary over time (variations up to 50% in the importance of the drivers) making it difficult to find a solid stationary system representation. Overall, we conclude that projection up to 2030 is only of use for quantifying impacts that act on a larger aggregation level, because at local level uncertainty is too large.

Theorizing Land Cover and Land Use Changes: The Case of Tropical Deforestation

NASA Technical Reports Server (NTRS)

Walker, Robert

2004-01-01

This article addresses land-cover and land-use dynamics from the perspective of regional science and economic geography. It first provides an account of the so-called spatially explicit model, which has emerged in recent years as a key empirical approach to the issue. The article uses this discussion as a springboard to evaluate the potential utility of von Thuenen to the discourse on land-cover and land-use change. After identifying shortcomings of current theoretical approaches to land use in mainly urban models, the article filters a discussion of deforestation through the lens of bid-rent and assesses its effectiveness in helping us comprehend the destruction of tropical forest in the Amazon basin. The article considers the adjustments that would have to be made to existing theory to make it more useful to the empirical issues.

Earth survey applications division: Research leading to the effective use of space technology in applications relating to the Earth's surface and interior

NASA Technical Reports Server (NTRS)

Carpenter, L. (Editor)

1980-01-01

Accomplishments and future plans are described for the following areas: (1) geology - geobotanical indicators and geopotential data; (2) modeling magnetic fields; (3) modeling the structure, composition, and evolution of the Earth's crust; (4) global and regional motions of the Earth's crust and earthquake occurrence; (5) modeling geopotential from satellite tracking data; (6) modeling the Earth's gravity field; (7) global Earth dynamics; (8) sea surface topography, ocean dynamics; and geophysical interpretation; (9) land cover and land use; (10) physical and remote sensing attributes important in detecting, measuring, and monitoring agricultural crops; (11) prelaunch studies using LANDSAT D; (12) the multispectral linear array; (13) the aircraft linear array pushbroom radiometer; and (14) the spaceborne laser ranging system.

Land Sea Level Difference Impacts on Socio-Hydrological System.

NASA Astrophysics Data System (ADS)

Sung, K.; Yu, D. J.; Oh, W. S.; Sangwan, N.

2016-12-01

Allowing moderate shocks can be a new solution that helps to build adaptive capacity in society is a rising issue. In Social-Ecological field, Carpenter et al. (2015) suggested that exposure to short-term variability leads to long term resilience by enlarging safe operating space (SOS). The SOS refers to the boundary of favorable state that ecosystem can maintain resilience without imposing certain conditions (Carpenter et al. 2015). Our work is motivated by defining SOS in socio-hydrological system(SHS) because it can be an alternative way for flood management beyond optimized or robust flood control. In this context, large flood events that make system to cross the SOS should be fully managed, but frequent small floods need to be allowed if the system is located in SOS. Especially, land sea level change is critical factor to change flood resilience since it is one of the most substantial disturbance that changes the entire boundary of SOS. In order to have broader perspective of vulnerability and resilience of the coastal region, it is crucial to understand the land sea level dynamics changed with human activities and natural variances.The risk of land sea level change has been researched , but most of these researches have focused on explain cause and effect of land sea level change, paying little attention to its dynamics interacts with human activities. Thus, an objective of this research is to study dynamics of human work, land sea level change and resilience to flood with SOS approach. Especially, we focus on the case in Ganges-Brahmaputra, Bangladesh where has high vulnerability to flood, and is faced with relatively rapid land sea level change problem. To acheive the goal, this study will develop a stylized model by extending the human - flood interaction model combined with relative sea level difference equation. The model describes the dynamics of flood protection system which is changed by SHS and land sea level chage. we will focus on the aggradation and human compaction which are highly chaged by human-flood interactions. Carpenter, S. R., W. A. Brock, C. Folke, E. H. van Nes, and M. Scheffer. 2015. Allowing variance may enlarge the safe operating space for exploited ecosystems. Proceedings of the National Academy of Sciences 112(46):14384-14389.

Modeled change in carbon balance between 1970-2100 of a polygonal arctic tundra ecosystem near Barrow, Alaska

NASA Astrophysics Data System (ADS)

Lara, M. J.; McGuire, A. D.; Euskirchen, E. S.; Sloan, V. L.; Iversen, C. M.; Norby, R. J.; Genet, H.; Zhang, Y.; Yuan, F.

2013-12-01

Northern permafrost regions are estimated to cover 16% of the global soil area and account for approximately 50% of the global belowground organic carbon pool. However, there are considerable uncertainties regarding the fate of this soil carbon pool with projected climate warming over the next century. In northern Alaska, nearly 65% of the terrestrial surface is composed of polygonal tundra, where microtopographic position (i.e. high center, low center, trough) varies surface hydrology, plant community composition, and biogeochemical cycling, over small (<5m) spatial scales. Due to large spatial heterogeneity and other non-linear responses of soil carbon to altered thermal regime, it is difficult to accurately estimate the fate of terrestrial carbon balance over decadal time-scales without explicitly considering the dynamically coupled processes driving permafrost dynamics, community structure, and ecosystem function. We use a new version of the terrestrial ecosystem model (TEM), which couples a dynamic vegetation and dynamic organic soil model (DVM-DOS-TEM). This large-scale ecosystem model is designed to study interactions among carbon and nitrogen cycling, vegetation composition, and soil physical properties, including permafrost and active layer dynamics. The model is parameterized and calibrated using data specific to the local climate, vegetation, and soils within various polygon land cover types (i.e. high center & rim, low center, trough) collected from sites (71.28°N 156.60° W) on the arctic coastal plain near Barrow, Alaska to estimate the likely change in carbon balance between 1970 and 2100 in this landscape. Model outputs are scaled across the Barrow Peninsula using the distribution of polygonal tundra land cover types, described by a land cover classification of 26.9 km2, using a 2008 multi-spectral QuickBird satellite image. The polygonal tundra land cover classification found high center & rims to represent 37.5% of the study area, low centers 19.7%, troughs 9.9%, water bodies (i.e. lakes, ponds, rivers) 17.8%, and non-polygonal tundra (i.e. drainage terraces & graminoid meadows) 15.1%, respectively. The overall accuracy of the map was 86%, based on 250 ground control points, and the Kappa coefficient was 0.77. Preliminary model runs for this region indicated variability in response to specific polygonal tundra land cover type through time. Overall, results suggest that it is important to consider discrete polygonal tundra features in regional estimates of carbon balance in northern Alaska.

Modelling Hydrology and Erosion in a Changing Socio-Economic Environment

NASA Astrophysics Data System (ADS)

Kirkby, M. J.; van Delden, H.; Hahn, B. M.; Irvine, B. J.

2009-12-01

Although forecasting systems have a limited time horizon due to the impact of unforeseen events, a rationally based model is able to provide some insights into likely short term behaviour, taking account of the dynamic interactions between climate, physical processes and land use decisions. The biophysical model (PESERA) takes land use decisions as inputs, together with climatic data or scenarios, topography and soils, to generate estimates of runoff, soil erosion, crop or natural vegetation growth and physical suitability, primarily based on crop yields. Estimates are made at a spatial resolution of 100 - 1000 m according to the area involved, the former for a catchment of say 1000 km2, the latter for a continental region. The generic dynamic land-use (change) model (METRONAMICA) has been fully integrated with PESERA to create the ‘Integrated Assessment Model’ (IAM) within the DESURVEY European project. The IAM takes biophysical performance and other spatial characteristics as an input and combines them with socio-economic data to determine potential suitability for each possible residential, commercial, agricultural etc use. The model then allocates each land use type and detailed agricultural class to the locations with the highest potential, based on neighbouring and historic choices as well as short-term economic advantage to estimate probabilities of change to alternative uses. Suitability, accessibility and zoning regulations are included in the decision process to provide the locational characteristics. Change of land use over time is thus determined within a cellular automaton model that generates rational spatial patterns of land use choice. The IAM is being applied at country scale in southern Europe and to smaller regions in North Africa. Although, in the long term, climate change is likely to dominate physical and economic impacts, in the shorter term over which this type of model can most reliably be used, the significance of land use change is much stronger.

Global simulation of interactions between groundwater and terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Braakhekke, M. C.; Rebel, K.; Dekker, S. C.; Smith, B.; Van Beek, L. P.; Sutanudjaja, E.; van Kampenhout, L.; Wassen, M. J.

2016-12-01

In many places in the world ecosystems are influenced by the presence of a shallow groundwater table. In these regions upward water flux due to capillary rise increases soil moisture availability in the root zone, which has strong positive effect on evapotranspiration. Additionally it has important consequences for vegetation dynamics and fluxes of carbon and nitrogen. Under water limited conditions shallow groundwater stimulates vegetation productivity, and soil organic matter decomposition while under saturated conditions groundwater may have a negative effect on these processes due to lack of oxygen. Furthermore, since plant species differ with respect to their root distribution, preference for moisture conditions, and resistance to oxygen stress, shallow groundwater also influences vegetation type. Finally, processes such as denitrification and methane production occur under strictly anaerobic conditions and are thus strongly influenced by moisture availability. Most global hydrological models and several land surface models simulate groundwater table dynamics and their effects on land surface processes. However, these models typically have relatively simplistic representation of vegetation and do not consider changes in vegetation type and structure and are therefore less suitable to represent effects of groundwater on biogeochemical fluxes. Dynamic global vegetation models (DGVMs), describe land surface from an ecological perspective, combining detailed description of vegetation dynamics and structure and biogeochemical processes. These models are thus more appropriate to simulate the ecological and biogeochemical effects of groundwater interactions. However, currently virtually all DGVMs ignore these effects, assuming that water tables are too deep to affect soil moisture in the root zone. We have implemented a tight coupling between the dynamic global ecosystem model LPJ-GUESS and the global hydrological model PCR-GLOBWB. Using this coupled model we aim to study the influence of shallow groundwater on terrestrial ecosystem processes. We will present results of global simulations to demonstrate the effects on C, N, and water fluxes.

Land-cover change research at the U.S. Geological Survey-assessing our nation's dynamic land surface

USGS Publications Warehouse

Wilson, Tamara S.

2011-01-01

The U.S. Geological Survey (USGS) recently completed an unprecedented, 27-year assessment of land-use and land-cover change for the conterminous United States. For the period 1973 to 2000, scientists generated estimates of change in major types of land use and land cover, such as development, mining, agriculture, forest, grasslands, and wetlands. To help provide the insight that our Nation will need to make land-use decisions in coming decades, the historical trends data is now being used by the USGS to help model potential future land use/land cover under different scenarios, including climate, environmental, economic, population, public policy, and technological change.

The Development of a Degree 360 Expansion of the Dynamic Ocean Topography of the POCM_4B Global Circulation Model

NASA Technical Reports Server (NTRS)

Rapp, Richard H.

1998-01-01

This paper documents the development of a degree 360 expansion of the dynamic ocean topography (DOT) of the POCM_4B ocean circulation model. The principles and software used that led to the final model are described. A key principle was the development of interpolated DOT values into land areas to avoid discontinuities at or near the land/ocean interface. The power spectrum of the POCM_4B is also presented with comparisons made between orthonormal (ON) and spherical harmonic magnitudes to degree 24. A merged file of ON and SH computed degree variances is proposed for applications where the DOT power spectrum from low to high (360) degrees is needed.

Characteristics of organic soil in black spruce forests: Implications for the application of land surface and ecosystem models in cold regions

USGS Publications Warehouse

Yi, S.; Manies, K.; Harden, J.; McGuire, A.D.

2009-01-01

Soil organic layers (OL) play an important role in landatmosphere exchanges of water, energy and carbon in cold environments. The proper implementation of OL in land surface and ecosystem models is important for predicting dynamic responses to climate warming. Based on the analysis of OL samples of black spruce (Picea mariana), we recommend that implementation of OL for cold regions modeling: (1) use three general organic horizon types (live, fibrous, and amorphous) to represent vertical soil heterogeneity; (2) implement dynamics of OL over the course of disturbance, as there are significant differences of OL thickness between young and mature stands; and (3) use two broad drainage classes to characterize spatial heterogeneity, as there are significant differences in OL thickness between dry and wet sites. Implementation of these suggestions into models has the potential to substantially improve how OL dynamics influence variability in surface temperature and soil moisture in cold regions. Copyright 2009 by the American Geophys.ical Union.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

14 CFR 29.562 - Emergency landing dynamic conditions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Emergency landing dynamic conditions. 29... Conditions § 29.562 Emergency landing dynamic conditions. (a) The rotorcraft, although it may be damaged in a... landing must successfully complete dynamic tests or be demonstrated by rational analysis based on dynamic...

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

NASA Astrophysics Data System (ADS)

Tang, G.; Bartlein, P. J.

2012-08-01

Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM) simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i) modify a DGVM for simulating land surface water balances; (ii) evaluate the modified model in simulating actual evapotranspiration (ET), soil moisture, and surface runoff at regional or watershed scales; and (iii) gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH) model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ) DGVM. To evaluate the model we ran LH using historical (1981-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981-2006 (R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficient > 0.52). The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences < 15%) with observed values for these rivers. Compared to a degree-day method for snowmelt computation, the addition of the solar radiation effect on snowmelt enabled LH to better simulate monthly stream flow in winter and early spring for rivers located at mid-to-high latitudes. In addition, LH-modeled monthly soil moisture for the state of Illinois (US) agreed well (R2 = 0.79, p < 0.01) with observed data for the years 1984-2001. Overall, this study justifies both the feasibility of incorporating satellite-based land covers into a DGVM and the reliability of LH to simulate land-surface water balances. To better estimate surface/river runoff at mid-to-high latitudes, we recommended that LPJ-DGVM considers the effects of solar radiation on snowmelt.

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

The changing phenology of the land carbon fluxes as derived from atmospheric CO2 data

NASA Astrophysics Data System (ADS)

Cescatti, A.; Alkama, R.; Forzieri, G.; Rödenbeck, C.; Zaehle, S.; Sitch, S.; Friedlingstein, P.; Nabel, J.; Viovy, N.; Kato, E.; Koven, C.; Zeng, N.; Ciais, P.

2017-12-01

Dynamic vegetation models and atmospheric observations of CO2 concentration point to a large increase of the global terrestrial carbon uptake over the recent decades. However, they disagree on the key regions, on the seasonality and on the processes underlying such a persistent increase. In particular, the role of the changing plant phenology on the global carbon budget is still unknown. To investigate these issues we explored the temporal dynamic of the land carbon fluxes over 1981-2014 using the Jena CarboScope atmospheric CO2 inversion and an ensemble of land surface models (TRENDY). Using these datasets the temporal extent and timing of the land carbon uptake and carbon release period have been investigated in four different latitudinal bands (75N-45N; 45N-15N; 15N-15S; 15S-45S) to explore the recent changes in the phenology of the vegetation CO2 exchange across different climates and biomes. The impact of phenological changes on the land carbon flux has been investigated by factoring out the signal due to the length of the growing season from the other signals. Estimates retrieved from the atmospheric inversion have been compared with the prediction of the ensemble of vegetation models. Results shows that the changes in the global carbon fluxes occurred in the last three decades are dominated by the duration and intensification of the uptake during the growing season. Interestingly, the seasonality of the trends shows a consistent pattern at all latitudinal bands, with a systematic advancement of the onset and minor changes of the end dates of the growing season. According to the atmospheric inversion the increasing trend in the land sink is driven about equally by the changes in phenology (due to the earlier onset and later offset) and by the intensification of the daily uptake. The increased annual carbon uptake revealed by the atmospheric inversion is about 60% larger than the model predictions, possibly due to the model underestimation of land use flues and poor representation of climate-driven changes in phenology. The observed large and persistent variations in the phenology of the terrestrial carbon fluxes emphasize the ongoing rapid changes in boreal and tropical biomes, whose dynamic response to climate change and rising CO2 concentration is still poorly represented in vegetation models.

Global change and terrestrial plant community dynamics

DOE PAGES

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; ...

2016-02-29

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less

Global change and terrestrial plant community dynamics

PubMed Central

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; Regan, Helen M.

2016-01-01

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this paper, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on a literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change. PMID:26929338

Flood projections within the Niger River Basin under future land use and climate change.

PubMed

Aich, Valentin; Liersch, Stefan; Vetter, Tobias; Fournet, Samuel; Andersson, Jafet C M; Calmanti, Sandro; van Weert, Frank H A; Hattermann, Fred F; Paton, Eva N

2016-08-15

This study assesses future flood risk in the Niger River Basin (NRB), for the first time considering the simultaneous effects of both projected climate change and land use changes. For this purpose, an ecohydrological process-based model (SWIM) was set up and validated for past climate and land use dynamics of the entire NRB. Model runs for future flood risks were conducted with an ensemble of 18 climate models, 13 of them dynamically downscaled from the CORDEX Africa project and five statistically downscaled Earth System Models. Two climate and two land use change scenarios were used to cover a broad range of potential developments in the region. Two flood indicators (annual 90th percentile and the 20-year return flood) were used to assess the future flood risk for the Upper, Middle and Lower Niger as well as the Benue. The modeling results generally show increases of flood magnitudes when comparing a scenario period in the near future (2021-2050) with a base period (1976-2005). Land use effects are more uncertain, but trends and relative changes for the different catchments of the NRB seem robust. The dry areas of the Sahelian and Sudanian regions of the basin show a particularly high sensitivity to climatic and land use changes, with an alarming increase of flood magnitudes in parts. A scenario with continuing transformation of natural vegetation into agricultural land and urbanization intensifies the flood risk in all parts of the NRB, while a "regreening" scenario can reduce flood magnitudes to some extent. Yet, land use change effects were smaller when compared to the effects of climate change. In the face of an already existing adaptation deficit to catastrophic flooding in the region, the authors argue for a mix of adaptation and mitigation efforts in order to reduce the flood risk in the NRB. Copyright © 2016 Elsevier B.V. All rights reserved.

Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal

USGS Publications Warehouse

Dieye, A.M.; Roy, David P.; Hanan, N.P.; Liu, S.; Hansen, M.; Toure, A.

2012-01-01

Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560 km2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.

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

NASA Astrophysics Data System (ADS)

Chen, Zemin

2007-06-01

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

Modeling the temporal dynamics of intertidal benthic infauna biomass with environmental factors: Impact assessment of land reclamation.

PubMed

Yang, Ye; Chui, Ting Fong May; Shen, Ping Ping; Yang, Yang; Gu, Ji Dong

2018-03-15

Anthropogenic activities such as land reclamation are threatening tidal marshes worldwide. This study's hypothesis is that land reclamation in a semi-enclosed bay alters the seasonal dynamics of intertidal benthic infauna, which is a key component in the tidal marsh ecosystem. Mai Po Tidal Marsh, Deep Bay, Pearl River Estuary, China was used as a case study to evaluate the hypothesis. Ecological models that simulate benthic biomass dynamics with governing environmental factors were developed, and various scenario experiments were conducted to evaluate the impact of reclamations. Environmental variables, selected from the areas of hydrodynamics, meteorology, and water quality based on correlation analysis, were used to generate Bayesian regression models for biomass prediction. The best-performing model, which considered average water age (i.e., a hydrodynamic indicator of estuarine circulation) in the previous month, salinity variation (i.e., standard deviation of salinity), and the total sunny period in the current month, captured well both seasonal and yearly trends in the benthic infauna observations from 2002 to 2008. This model was then used to simulate biomass dynamics with varying inputs of water age and salinity variation from coastal numerical models of different reclamation scenarios. The simulation results suggest that the reclamation in 2007 decreased the spatial and annual average benthic infauna biomass in the tidal marsh by 20%, which agreed with the 28% biomass decrease recorded by field survey. The range of biomass seasonal variation also decreased significantly from 2.1 to 230.5g/m 2 (without any reclamation) to 1.2 to 131.1g/m 2 (after the 2007 reclamation), which further demonstrates the substantial ecological impact of reclamation. The ecological model developed in this study could simulate seasonal biomass dynamics and evaluate the ecological impact of reclamation projects. It can therefore be applied to evaluate the ecological impact of coastal engineering projects for tidal marsh management, conservation, and restoration. Copyright © 2017 Elsevier B.V. All rights reserved.

A new concept for simulation of vegetated land surface dynamics - Part 1: The event driven phenology model

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Henebry, G. M.

2012-01-01

Phenologies of the vegetated land surface are being used increasingly for diagnosis and prognosis of climate change consequences. Current prospective and retrospective phenological models stand far apart in their approaches to the subject. We report on an exploratory attempt to implement a phenological model based on a new event driven concept which has both diagnostic and prognostic capabilities in the same modeling framework. This Event Driven Phenological Model (EDPM) is shown to simulate land surface phenologies and phenophase transition dates in agricultural landscapes based on assimilation of weather data and land surface observations from spaceborne sensors. The model enables growing season phenologies to develop in response to changing environmental conditions and disturbance events. It also has the ability to ingest remotely sensed data to adjust its output to improve representation of the modeled variable. We describe the model and report results of initial testing of the EDPM using Level 2 flux tower records from the Ameriflux sites at Mead, Nebraska, USA, and at Bondville, Illinois, USA. Simulating the dynamics of normalized difference vegetation index based on flux tower data, the predictions by the EDPM show good agreement (RMSE < 0.08; r2 > 0.8) for maize and soybean during several growing seasons at different locations. This study presents the EDPM used in the companion paper (Kovalskyy and Henebry, 2011) in a coupling scheme to estimate daily actual evapotranspiration over multiple growing seasons.

A new concept for simulation of vegetated land surface dynamics - Part 1: The event driven phenology model

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Henebry, G. M.

2011-05-01

Phenologies of the vegetated land surface are being used increasingly for diagnosis and prognosis of climate change consequences. Current prospective and retrospective phenological models stand far apart in their approaches to the subject. We report on an exploratory attempt to implement a phenological model based on a new event driven concept which has both diagnostic and prognostic capabilities in the same modeling framework. This Event Driven Phenological Model (EDPM) is shown to simulate land surface phenologies and phenophase transition dates in agricultural landscapes based on assimilation of weather data and land surface observations from spaceborne sensors. The model enables growing season phenologies to develop in response to changing environmental conditions and disturbance events. It also has the ability to ingest remotely sensed data to adjust its output to improve representation of the modeled variable. We describe the model and report results of initial testing of the EDPM using Level 2 flux tower records from the Ameriflux sites at Mead, Nebraska, USA, and at Bondville, Illinois, USA. Simulating the dynamics of normalized difference vegetation index based on flux tower data, the predictions by the EDPM show good agreement (RMSE < 0.08; r2>0.8) for maize and soybean during several growing seasons at different locations. This study presents the EDPM used in the companion paper (Kovalskyy and Henebry, 2011) in a coupling scheme to estimate daily actual evapotranspiration over multiple growing seasons.

Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change.

PubMed

Feng, Yongjiu; Tong, Xiaohua

2017-09-22

Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.

Properties of a center/surround retinex. Part 2: Surround design

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.; Woodell, Glenn A.

1995-01-01

The last version of Edwin Land's retinex model for human vision's lightness and color constancy has been implemented. Previous research has established the mathematical foundations of Land's retinex but has not examined specific design issues and their effects on the properties of the retinex operation. We have sought to define a practical implementation of the retinex without particular concern for its validity as a model for human lightness and color perception. Here we describe issues involved in designing the surround function. We find that there is a trade-off between rendition and dynamic range compression that is governed by the surround space constant. Various functional forms for the retinex surround are evaluated and a Gaussian form is found to perform better than the inverse square suggested by Land. Preliminary testing led to the design of a Gaussian surround with a space constant of 80 pixels as a reasonable compromise between dynamic range compression and rendition.

Growth of Ni nanoclusters on irradiated graphene: a molecular dynamics study.

PubMed

Valencia, F J; Hernandez-Vazquez, E E; Bringa, E M; Moran-Lopez, J L; Rogan, J; Gonzalez, R I; Munoz, F

2018-04-23

We studied the soft landing of Ni atoms on a previously damaged graphene sheet by means of molecular dynamics simulations. We found a monotonic decrease of the cluster frequency as a function of its size, but few big clusters comprise an appreciable fraction of the total number of Ni atoms. The aggregation of Ni atoms is also modeled by means of a simple phenomenological model. The results are in clear contrast with the case of hard or energetic landing of metal atoms, where there is a tendency to form mono-disperse metal clusters. This behavior is attributed to the high diffusion of unattached Ni atoms, together with vacancies acting as capture centers. The findings of this work show that a simple study of the energetics of the system is not enough in the soft landing regime, where it is unavoidable to also consider the growth process of metal clusters.

A Brief Investigation of the Hydrodynamic Characteristics of a 1/13.33-Scale Powered Dynamic Model of a Preliminary Design of the Martin XP6M-1 Flying Boat, TED No. NACA DE-385

NASA Technical Reports Server (NTRS)

Blanchard, Ulysse J.

1953-01-01

The hydrodynamic characteristics of a preliminary design of the Martin XP6M-1 flying boat have been determined. Longitudinal stability during take-off and landing, resistance of the complete model, and behavior during taxiing and landing in rough water are presented.

A vertically integrated snow/ice model over land/sea for climate models. I - Development. II - Impact on orbital change experiments

NASA Technical Reports Server (NTRS)

Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

1988-01-01

A vertically integrated formulation (VIF) model for sea ice/snow and land snow is discussed which can simulate the nonlinear effects of heat storage and transfer through the layers of snow and ice. The VIF demonstates the accuracy of the multilayer formulation, while benefitting from the computational flexibility of linear formulations. In the second part, the model is implemented in a seasonal dynamic zonally averaged climate model. It is found that, in response to a change between extreme high and low summer insolation orbits, the winter orbital change dominates over the opposite summer change for sea ice. For snow over land the shorter but more pronounced summer orbital change is shown to dominate.

Land-atmosphere coupling and soil moisture memory contribute to long-term agricultural drought

NASA Astrophysics Data System (ADS)

Kumar, S.; Newman, M.; Lawrence, D. M.; Livneh, B.; Lombardozzi, D. L.

2017-12-01

We assessed the contribution of land-atmosphere coupling and soil moisture memory on long-term agricultural droughts in the US. We performed an ensemble of climate model simulations to study soil moisture dynamics under two atmospheric forcing scenarios: active and muted land-atmosphere coupling. Land-atmosphere coupling contributes to a 12% increase and 36% decrease in the decorrelation time scale of soil moisture anomalies in the US Great Plains and the Southwest, respectively. These differences in soil moisture memory affect the length and severity of modeled drought. Consequently, long-term droughts are 10% longer and 3% more severe in the Great Plains, and 15% shorter and 21% less severe in the Southwest. An analysis of Coupled Model Intercomparsion Project phase 5 data shows four fold uncertainty in soil moisture memory across models that strongly affects simulated long-term droughts and is potentially attributable to the differences in soil water storage capacity across models.

Intermodel spread of the double-ITCZ bias in coupled GCMs tied to land surface temperature in AMIP GCMs

NASA Astrophysics Data System (ADS)

Zhou, Wenyu; Xie, Shang-Ping

2017-08-01

Global climate models (GCMs) have long suffered from biases of excessive tropical precipitation in the Southern Hemisphere (SH). The severity of the double-Intertropical Convergence Zone (ITCZ) bias, defined here as the interhemispheric difference in zonal mean tropical precipitation, varies strongly among models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble. Models with a more severe double-ITCZ bias feature warmer tropical sea surface temperature (SST) in the SH, coupled with weaker southeast trades. While previous studies focus on coupled ocean-atmosphere interactions, here we show that the intermodel spread in the severity of the double-ITCZ bias is closely related to land surface temperature biases, which can be further traced back to those in the Atmosphere Model Intercomparison Project (AMIP) simulations. By perturbing land temperature in models, we demonstrate that cooler land can indeed lead to a more severe double-ITCZ bias by inducing the above coupled SST-trade wind pattern in the tropics. The response to land temperature can be consistently explained from both the dynamic and energetic perspectives. Although this intermodel spread from the land temperature variation does not account for the ensemble model mean double-ITCZ bias, identifying the land temperature effect provides insights into simulating a realistic ITCZ for the right reasons.

Land Conversion in Amazonia and Northern South America; Influences on Regional Hydrology and Ecosystem Response

NASA Astrophysics Data System (ADS)

Knox, Ryan Gary

A numerical model of the terrestrial biosphere (Ecosystem Demography Model) is compbined with an atmospheric model (Brazilian Regional Atmospheric Modeling System) to investigate how land conversion in the Amazon and Northern South America have changed the hydrology of the region, and to see if those changes are significant enough to produce an ecological response. Two numerical realizations of the structure and composition of terrestrial vegetation are used as boundary conditions in a simulation of the regional land surface and atmosphere. One realization seeks to capture the present day vegetation condition that includes human deforestation and land-conversion, the other is an estimate of the potential structure and composition of the region without human influence. Model output is assessed for consistent and significant differences in hydrometeorology. Locations that show compelling differences are taken as case studies. The seasonal biases in precipitation at these locations are then used to create perturbations to long-term climate datasets. These perturbations then drive long-term simulations of dynamic vegetation to see if the climate consistent with a potential regional vegetation could elicit a change in the vegetation equilibrium at the site. Results show that South American land conversion has had consistent impacts on the regional patterning of precipitation. At some locations, changes in precipitation are persistent and constitute a significant fraction of total precipitation. Land-conversion has decreased mean continental evaporation and increased mean moisture convergence. Case study simulations of long term vegetation dynamic indicate that a hydrologic climate consistent with regional potential vegetation can indeed have significant influence on ecosystem structure and composition, particularly in water limited growth conditions. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs@mit.edu)

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.

A novel assessment of the role of land-use and land-cover change in the global carbon cycle, using a new Dynamic Global Vegetation Model version of the CABLE land surface model

NASA Astrophysics Data System (ADS)

Haverd, Vanessa; Smith, Benjamin; Nieradzik, Lars; Briggs, Peter; Canadell, Josep

2017-04-01

In recent decades, terrestrial ecosystems have sequestered around 1.2 PgC y-1, an amount equivalent to 20% of fossil-fuel emissions. This land carbon flux is the net result of the impact of changing climate and CO2 on ecosystem productivity (CO2-climate driven land sink ) and deforestation, harvest and secondary forest regrowth (the land-use change (LUC) flux). The future trajectory of the land carbon flux is highly dependent upon the contributions of these processes to the net flux. However their contributions are highly uncertain, in part because the CO2-climate driven land sink and LUC components are often estimated independently, when in fact they are coupled. We provide a novel assessment of global land carbon fluxes (1800-2015) that integrates land-use effects with the effects of changing climate and CO2 on ecosystem productivity. For this, we use a new land-use enabled Dynamic Global Vegetation Model (DGVM) version of the CABLE land surface model, suitable for use in attributing changes in terrestrial carbon balance, and in predicting changes in vegetation cover and associated effects on land-atmosphere exchange. In this model, land-use-change is driven by prescribed gross land-use transitions and harvest areas, which are converted to changes in land-use area and transfer of carbon between pools (soil, litter, biomass, harvested wood products and cleared wood pools). A novel aspect is the treatment of secondary woody vegetation via the coupling between the land-use module and the POP (Populations Order Physiology) module for woody demography and disturbance-mediated landscape heterogeneity. Land-use transitions to and from secondary forest tiles modify the patch age distribution within secondary-vegetated tiles, in turn affecting biomass accumulation and turnover rates and hence the magnitude of the secondary forest sink. The resulting secondary forest patch age distribution also influences the magnitude of the secondary forest harvest and clearance fluxes, with oldest patches (high biomass) being preferentially harvested, and youngest patches (low biomass) being preferentially cleared. Our results, which agree well with the net land flux derived from the global carbon budget, are used for a process-attribution of the land carbon sink. Use of multiple constraints provides confidence in our process-attribution: we use observation-based data sets to evaluate predictions of global spatial distributions of vegetation cover, evaporation, gross primary production, biomass and soil carbon; interannual variability of the global terrestrial carbon sink; forest allometric relations and age-effects on net primary production.

An AD100 implementation of a real-time STOVL aircraft propulsion system

NASA Technical Reports Server (NTRS)

Ouzts, Peter J.; Drummond, Colin K.

1990-01-01

A real-time dynamic model of the propulsion system for a Short Take-Off and Vertical Landing (STOVL) aircraft was developed for the AD100 simulation environment. The dynamic model was adapted from a FORTRAN based simulation using the dynamic programming capabilities of the AD100 ADSIM simulation language. The dynamic model includes an aerothermal representation of a turbofan jet engine, actuator and sensor models, and a multivariable control system. The AD100 model was tested for agreement with the FORTRAN model and real-time execution performance. The propulsion system model was also linked to an airframe dynamic model to provide an overall STOVL aircraft simulation for the purposes of integrated flight and propulsion control studies. An evaluation of the AD100 system for use as an aircraft simulation environment is included.

Incorporating dynamic root growth enhances the performance of Noah-MP at two contrasting winter wheat field sites

NASA Astrophysics Data System (ADS)

Gayler, Sebastian; Wöhling, Thomas; Ingwersen, Joachim; Wizemann, Hans-Dieter; Warrach-Sagi, Kirsten; Attinger, Sabine; Streck, Thilo; Wulmeyer, Volker

2014-05-01

Interactions between the soil, the vegetation, and the atmospheric boundary layer require close attention when predicting water fluxes in the hydrogeosystem, agricultural systems, weather and climate. However, land-surface schemes used in large scale models continue to show deficits in consistently simulating fluxes of water and energy from the subsurface through vegetation layers to the atmosphere. In this study, the multi-physics version of the Noah land-surface model (Noah-MP) was used to identify the processes, which are most crucial for a simultaneous simulation of water and heat fluxes between land-surface and the lower atmosphere. Comprehensive field data sets of latent and sensible heat fluxes, ground heat flux, soil moisture, and leaf area index from two contrasting field sites in South-West Germany are used to assess the accuracy of simulations. It is shown that an adequate representation of vegetation-related processes is the most important control for a consistent simulation of energy and water fluxes in the soil-plant-atmosphere system. In particular, using a newly implemented sub-module to simulate root growth dynamics has enhanced the performance of Noah-MP at both field sites. We conclude that further advances in the representation of leaf area dynamics and root/soil moisture interactions are the most promising starting points for improving the simulation of feedbacks between the sub-soil, land-surface and atmosphere in fully-coupled hydrological and atmospheric models.

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.

Present and future of desertification in Spain: Implementation of a surveillance system to prevent land degradation.

PubMed

Martínez-Valderrama, Jaime; Ibáñez, Javier; Del Barrio, Gabriel; Sanjuán, Maria E; Alcalá, Francisco J; Martínez-Vicente, Silvio; Ruiz, Alberto; Puigdefábregas, Juan

2016-09-01

Mitigation strategies are crucial for desertification given that once degradation starts, other solutions are extremely expensive or unworkable. Prevention is key to handle this problem and solutions should be based on spotting and deactivating the stressors of the system. Following this topic, the Spanish Plan of Action to Combat Desertification (SPACD) created the basis for implementing two innovative approaches to evaluate the threat of land degradation in the country. This paper presents tools for preventing desertification in the form of a geomatic approach to enable the periodic assessments of the status and trends of land condition. Also System Dynamics modelling has been used to integrate bio-physical and socio-economic aspects of desertification to explain and analyse degradation in the main hot spots detected in Spain. The 2dRUE procedure was implemented to map the land-condition status by comparing potential land productivity according to water availability, the limiting factor in arid lands, with plant-biomass data. This assessment showed that 20% of the territory is degraded and an additional 1% is actively degrading. System Dynamics modelling was applied to study the five desertification landscapes identified by the SPACD. The risk analysis, implemented on these models, concluded that 'Herbaceous crops affected by soil erosion' is the landscape most at risk, while the Plackett-Burman sensitivity analysis used to rank the factors highlighted the supremacy of climatic factors above socioeconomic drivers. Copyright © 2016 Elsevier B.V. All rights reserved.

Integrated Dynamic Gloabal Modeling of Land Use, Energy and Economic Growth

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

Atul Jain, University of Illinois, Urbana-Champaign, IL

2009-10-14

The overall objective of this collaborative project is to integrate an existing general equilibrium energy-economic growth model with a biogeochemical cycles and biophysical models in order to more fully explore the potential contribution of land use-related activities to future emissions scenarios. Land cover and land use change activities, including deforestation, afforestation, and agriculture management, are important source of not only CO2, but also non-CO2 GHGs. Therefore, contribution of land-use emissions to total emissions of GHGs is important, and consequently their future trends are relevant to the estimation of climate change and its mitigation. This final report covers the full projectmore » period of the award, beginning May 2006, which includes a sub-contract to Brown University later transferred to the National Center for Atmospheric Research (NCAR) when Co-PI Brian O'Neill changed institutional affiliations.« less

Using WEED to simulate the global wetland distribution in a ESM

NASA Astrophysics Data System (ADS)

Stacke, Tobias; Hagemann, Stefan

2016-04-01

Lakes and wetlands are an important land surface feature. In terms of hydrology, they regulate river discharge, mitigate flood events and constitute a significant surface water storage. Considering physical processes, they link the surface water and energy balances by altering the separation of incoming energy into sensible and latent heat fluxes. Finally, they impact biogeochemical processes and may act as carbon sinks or sources. Most global hydrology and climate models regard wetland extent and properties as constant in time. However, to study interactions between wetlands and different states of climate, it is necessary to implement surface water bodies (thereafter referred to as wetlands) with dynamical behavior into these models. Besides an improved representation of geophysical feedbacks between wetlands, land surface and atmosphere, a dynamical wetland scheme could also provide estimates of soil wetness as input for biogeochemical models, which are used to compute methane production in wetlands. Recently, a model for the representation of wetland extent dynamics (WEED) was developed as part of the hydrology model (MPI-HM) of the Max-Planck-Institute for Meteorology (MPI-M). The WEED scheme computes wetland extent in agreement with the range of observations for the high northern latitudes. It simulates a realistic seasonal cycle which shows sensitivity to northern snow-melt as well as rainy seasons in the tropics. Furthermore, flood peaks in river discharge are mitigated. However, the WEED scheme overestimates wetland extent in the Tropics which might be related to the MPI-HM's simplified potential evapotranspiration computation. In order to overcome this limitation, the WEED scheme is implemented into the MPI-M's land surface model JSBACH. Thus, not only its effect on water fluxes can be investigated but also its impact on the energy cycle, which is not included in the MPI-HM. Furthermore, it will be possible to analyze the physical effects of wetlands in a coupled land-atmosphere simulation. First simulations with JSBACH-WEED show results similar to the MPI-HM simulations. As the next step, the scheme is modified to account for energy cycle relevant issues such as the dynamical alteration of surface albedo as well as the allocation of appropriate thermal properties to the wetlands. In our presentation, we will give an overview on the functionality of the WEED scheme and the effect of wetlands in coupled land-atmosphere simulations.

Dynamics and resilience in interdependent systems at the energy-water-land nexus

NASA Astrophysics Data System (ADS)

Moss, R. H.

2017-12-01

Water resources management is already complex enough, given fragmented landscapes and institutions and uncertain climate and environmental conditions. But given the interdependence of water, energy, and land systems (the "energy-water-land nexus"), integrated approaches to cross-sectoral modeling and decision making that account for the interdependencies are increasingly important. This presentation will describe the context of the broader institutional and policy dimensions (e.g., cross-Federal research agencies) and scientific challenges of bringing the water, energy, and land research communities together (e.g., different epistemologies, data, modeling, and decision support methods). The speaker will describe efforts to develop a shared community of practice to improve research collaboration and provide insights on coupled system resilience.

Modeling the potential persistence of various ecological systems under CMIP5 future climate and land use scenarios throughout California, USA

NASA Astrophysics Data System (ADS)

Baker, B.; Ferschweiler, K.; Bachelet, D. M.; Sleeter, B. M.

2016-12-01

California's geographic location, topographic complexity and latitudinal climatic gradient give rise to great biological and ecological diversity. However, increased land use pressure, altered seasonal weather patterns, and changes in temperature and precipitation regimes are having pronounced effects on ecosystems and the multitude of services they provide for an increasing population. As a result, natural resource managers are faced with formidable challenges to maintain these critical services. The goals of this project were to better understand how projected 21st century climate and land-use change scenarios may alter ecosystem dynamics, the spatial distribution of various vegetation types and land-use patterns, and to provide a coarse scale "triage map" of where land managers may want to concentrate efforts to reduce ecological stress in order to mitigate the potential impacts of a changing climate. We used the MC2 dynamic global vegetation model and the LUCAS state-and-transition simulation model to simulate the potential effects of future climate and land-use change on ecological processes for the state of California. Historical climate data were obtained from the PRISM dataset and nine CMIP5 climate models were run for the RCP 8.5 scenario. Climate projections were combined with a business-as-usual land-use scenario based on local-scale land use histories. For ease of discussion, results from five simulation runs (historic, hot-dry, hot-wet, warm-dry, and warm-wet) are presented. Results showed large changes in the extent of urban and agricultural lands. In addition, several simulated potential vegetation types persisted in situ under all four future scenarios, although alterations in total area, total ecosystem carbon, and forest vigor (NPP/LAI) were noted. As might be expected, the majority of the forested types that persisted occurred on public lands. However, more than 78% of the simulated subtropical mixed forest and 26% of temperate evergreen needleleaf forest types persisted on private lands under all four future scenarios. Result suggest that building collaborations across management borders could be valuable tool to guide natural resource management actions into the future.

Viability of Cross-Flow Fan with Helical Blades for Vertical Take-off and Landing Aircraft

DTIC Science & Technology

2012-09-01

fluid dynamics (CFD) software, ANSYS - CFX , a three-dimensional (3-D) straight-bladed model was validated against previous study’s experimental results...computational fluid dynamics software (CFD), ANSYS - CFX , a three-dimensional (3-D) straight-bladed model was validated against previous study’s experimental...37 B. SIZING PARAMETERS AND ILLUSTRATION ................................. 37 APPENDIX B. ANSYS CFX PARAMETERS

Modeling snag dynamics in northern Arizona mixed-conifer and ponderosa pine forests

Treesearch

Joseph L. Ganey; Scott C. Vojta

2007-01-01

Snags (standing dead trees) are important components of forested habitats that contribute to ecological decay and recycling processes as well as providing habitat for many life forms. As such, snags are of special interest to land managers, but information on dynamics of snag populations is lacking. We modeled trends in snag populations in mixed-conifer and ponderosa...

Endangered Butterflies as a Model System for Managing Source Sink Dynamics on Department of Defense Lands

DTIC Science & Technology

patches to cycle from sink to source status and back.Objective: Through a combination of field studies and state-of-the-art quantitative models, we...landscapes with dynamic changes in habitat quality due to management. We also validated our general approach by comparing patterns in our focal species to general, cross-taxa, patterns.

Temporal dynamics of land use/land cover change and its prediction using CA-ANN model for southwestern coastal Bangladesh.

PubMed

Rahman, M Tauhid Ur; Tabassum, Faheemah; Rasheduzzaman, Md; Saba, Humayra; Sarkar, Lina; Ferdous, Jannatul; Uddin, Syed Zia; Zahedul Islam, A Z M

2017-10-17

Change analysis of land use and land cover (LULC) is a technique to study the environmental degradation and to control the unplanned development. Analysis of the past changing trend of LULC along with modeling future LULC provides a combined opportunity to evaluate and guide the present and future land use policy. The southwest coastal region of Bangladesh, especially Assasuni Upazila of Satkhira District, is the most vulnerable to natural disasters and has faced notable changes in its LULC due to the combined effects of natural and anthropogenic causes. The objectives of this study are to illustrate the temporal dynamics of LULC change in Assasuni Upazila over the last 27 years (i.e., between 1989 and 2015) and also to predict future land use change using CA-ANN (cellular automata and artificial neural network) model for the year 2028. Temporal dynamics of LULC change was analyzed, employing supervised classification of multi-temporal Landsat images. Then, prediction of future LULC was carried out by CA-ANN model using MOLUSCE plugin of QGIS. The analysis of LULC change revealed that the LULC of Assasuni had changed notably during 1989 to 2015. "Bare lands" decreased by 21% being occupied by other land uses, especially by "shrimp farms." Shrimp farm area increased by 25.9% during this period, indicating a major occupational transformation from agriculture to shrimp aquaculture in the study area during the period under study. Reduction in "settlement" area revealed the trend of migration from the Upazila. The predicted LULC for the year 2028 showed that reduction in bare land area would continue and 1595.97 ha bare land would transform into shrimp farm during 2015 to 2028. Also, the impacts of the changing LULC on the livelihood of local people and migration status of the Upazila were analyzed from the data collected through focus group discussions and questionnaire surveys. The analysis revealed that the changing LULC and the occupational shift from paddy cultivation to shrimp farming were related to each other. Around 31.3% of the total respondents stated that at least one of their family members had migrated. Climate-driven southwestern coastal people usually migrate from the vulnerable rural areas towards the nearest relatively safe city due to adverse effects of natural disasters. To control the unplanned development and reduce the internal migration in Assasuni and other coastal areas, a comprehensive land use management plan was suggested that would accommodate the diversified uses of coastal lands and eventually lessen the threats to the life and livelihood of the local people.

14 CFR 23.562 - Emergency landing dynamic conditions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Emergency Landing Conditions § 23.562 Emergency landing dynamic conditions. (a) Each seat/restraint system... dynamic tests conducted in accordance with paragraph (b) of this section: (1) The seat/restraint system... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Emergency landing dynamic conditions. 23...

Connecting the Mississippi River with Carbon Variability in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Xue, Z. G.; He, R.; Fennel, K.; Cai, W. J.; Lohrenz, S. E.; Huang, W. J.; Tian, H.; Ren, W.

2016-02-01

To understand the linkage between landuse/land-cover change within the Mississippi basin and the carbon dynamics in the Gulf of Mexico, a three-dimensional coupled physical-biogeochemical model was used to the examine temporal and spatial variability of surface ocean pCO2 in the Gulf of Mexico (GoM). The model is driven by realistic atmospheric forcing, open boundary conditions from a data-assimilative global ocean circulation model, and freshwater and terrestrial nutrient and carbon input from major rivers provided by the Dynamic Land Ecosystem Model (DLEM). A seven-year model hindcast (2004-2010) was performed and was validated against the recently updated Lamont-Doherty Earth Observatory global ocean carbon dataset. Model simulated seawater pCO2 and air-sea CO2 flux are in good agreement with in-situ measurements. An inorganic carbon budget was estimated based on the multi-year mean of the model results. Overall, the GoM is a sink of atmospheric CO2 with a flux of 0.92 × 1012 mol C yr-1, which, together with the enormous fluvial carbon input, is balanced by carbon export through the Loop Current. In a sensitivity experiment with all biological sources and sinks of carbon disabled surface pCO2 was elevated by 70 ppm, suggesting that biological uptake is the most important reason for the simulated CO2 sink. The impact from landuse and land-cover changes within the Mississippi River basin on coastal pCO2 dynamics is also discussed based on a scenario run driven by river conditions during the 1904-1910 provided by the DLEM model.

Developing a Dynamic SPARROW Water Quality Decision Support System Using NASA Remotely-Sensed Products

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Smith, R. A.; Hoos, A.; Schwarz, G. E.; Alexander, R. B.; Crosson, W. L.; Srikishen, J.; Estes, M., Jr.; Cruise, J.; Al-Hamdan, A.; Ellenburg, W. L., II; Flores, A.; Sanford, W. E.; Zell, W.; Reitz, M.; Miller, M. P.; Journey, C. A.; Befus, K. M.; Swann, R.; Herder, T.; Sherwood, E.; Leverone, J.; Shelton, M.; Smith, E. T.; Anastasiou, C. J.; Seachrist, J.; Hughes, A.; Graves, D.

2017-12-01

The USGS Spatially Referenced Regression on Watershed Attributes (SPARROW) surface water quality modeling system has been widely used for long term, steady state water quality analysis. However, users have increasingly requested a dynamic version of SPARROW that can provide seasonal estimates of nutrients and suspended sediment to receiving waters. The goal of this NASA-funded project is to develop a dynamic decision support system to enhance the southeast SPARROW water quality model and finer-scale dynamic models for selected coastal watersheds through the use of remotely-sensed data and other NASA Land Information System (LIS) products. The spatial and temporal scale of satellite remote sensing products and LIS modeling data make these sources ideal for the purposes of development and operation of the dynamic SPARROW model. Remote sensing products including MODIS vegetation indices, SMAP surface soil moisture, and OMI atmospheric chemistry along with LIS-derived evapotranspiration (ET) and soil temperature and moisture products will be included in model development and operation. MODIS data will also be used to map annual land cover/land use in the study areas and in conjunction with Landsat and Sentinel to identify disturbed areas that might be sources of sediment and increased phosphorus loading through exposure of the bare soil. These data and others constitute the independent variables in a regression analysis whose dependent variables are the water quality constituents total nitrogen, total phosphorus, and suspended sediment. Remotely-sensed variables such as vegetation indices and ET can be proxies for nutrient uptake by vegetation; MODIS Leaf Area Index can indicate sources of phosphorus from vegetation; soil moisture and temperature are known to control rates of denitrification; and bare soil areas serve as sources of enhanced nutrient and sediment production. The enhanced SPARROW dynamic models will provide improved tools for end users to manage water quality in near real time and for the formulation of future scenarios to inform strategic planning. Time-varying SPARROW outputs will aid water managers in decision making regarding allocation of resources in protecting aquatic habitats, planning for harmful algal blooms, and restoration of degraded habitats, stream segments, or lakes.

Alternative stable states and the sustainability of forests, grasslands, and agriculture

PubMed Central

Henderson, Kirsten A.; Bauch, Chris T.; Anand, Madhur

2016-01-01

Endangered forest–grassland mosaics interspersed with expanding agriculture and silviculture occur across many parts of the world, including the southern Brazilian highlands. This natural mosaic ecosystem is thought to reflect alternative stable states driven by threshold responses of recruitment to fire and moisture regimes. The role of adaptive human behavior in such systems remains understudied, despite its pervasiveness and the fact that such ecosystems can exhibit complex dynamics. We develop a nonlinear mathematical model of coupled human–environment dynamics in mosaic systems and social processes regarding conservation and economic land valuation. Our objective is to better understand how the coupled dynamics respond to changes in ecological and social conditions. The model is parameterized with southern Brazilian data on mosaic ecology, land-use profits, and questionnaire results concerning landowner preferences and conservation values. We find that the mosaic presently resides at a crucial juncture where relatively small changes in social conditions can generate a wide variety of possible outcomes, including complete loss of mosaics; large-amplitude, long-term oscillations between land states that preclude ecosystem stability; and conservation of the mosaic even to the exclusion of agriculture/silviculture. In general, increasing the time horizon used for conservation decision making is more likely to maintain mosaic stability. In contrast, increasing the inherent conservation value of either forests or grasslands is more likely to induce large oscillations—especially for forests—due to feedback from rarity-based conservation decisions. Given the potential for complex dynamics, empirically grounded nonlinear dynamical models should play a larger role in policy formulation for human–environment mosaic ecosystems. PMID:27956605

Alternative stable states and the sustainability of forests, grasslands, and agriculture.

PubMed

Henderson, Kirsten A; Bauch, Chris T; Anand, Madhur

2016-12-20

Endangered forest-grassland mosaics interspersed with expanding agriculture and silviculture occur across many parts of the world, including the southern Brazilian highlands. This natural mosaic ecosystem is thought to reflect alternative stable states driven by threshold responses of recruitment to fire and moisture regimes. The role of adaptive human behavior in such systems remains understudied, despite its pervasiveness and the fact that such ecosystems can exhibit complex dynamics. We develop a nonlinear mathematical model of coupled human-environment dynamics in mosaic systems and social processes regarding conservation and economic land valuation. Our objective is to better understand how the coupled dynamics respond to changes in ecological and social conditions. The model is parameterized with southern Brazilian data on mosaic ecology, land-use profits, and questionnaire results concerning landowner preferences and conservation values. We find that the mosaic presently resides at a crucial juncture where relatively small changes in social conditions can generate a wide variety of possible outcomes, including complete loss of mosaics; large-amplitude, long-term oscillations between land states that preclude ecosystem stability; and conservation of the mosaic even to the exclusion of agriculture/silviculture. In general, increasing the time horizon used for conservation decision making is more likely to maintain mosaic stability. In contrast, increasing the inherent conservation value of either forests or grasslands is more likely to induce large oscillations-especially for forests-due to feedback from rarity-based conservation decisions. Given the potential for complex dynamics, empirically grounded nonlinear dynamical models should play a larger role in policy formulation for human-environment mosaic ecosystems.

The Ancient Maya Landscape: Facing the Challenges and Embracing the Promise of Integrating Archaeology, Remote Sensing, Soil Science and Hydrologic Modeling for Coupled Natural and Human Systems.

NASA Astrophysics Data System (ADS)

Murtha, T., Jr.; Duffy, C.; Cook, B. D.; Schroder, W.; Webster, D.; French, K. D.; Alcover, O.; Golden, C.; Balzotti, C.; Shaffer, D.

2016-12-01

Relying on a niche inheritance perspective, this paper discusses the long-term spatial and temporal dynamics of land-use management, agricultural decision making and patterns of resource availability in the tropical lowlands of Central America. We introduce and describe ongoing research that addresses a series of long standing questions about coupled natural and human history dynamics in the Central Maya lowlands, emphasizing the role of landscape and region to address these questions. First, we summarize the results of a CNH pilot study focused on the evolution of the regional landscape of Tikal, Guatemala. Particular attention is centered on how we integrated landscape survey, traditional archaeology and soil studies to understand the spatial and temporal dynamics of agricultural land use and intensification over a two thousand period. Additionally, we discuss how these results were integrated into remote sensing, hydrological and erosion models to better understand how past changes in available water and productive land compare to what we know about settlement patterns in the Tikal Region over that same time period. We not only describe how the Maya transformed this landscape, but also how the region influenced changing patterns of settlement and land use. We finish this section with a discussion of some of the unique challenges integrating archaeological information to study CNH dynamics during this pilot study. Second, we introduce a new project designed to `scale up' the pilot study for a macro-regional analysis of the lowland Maya landscape. The new project leverages a uniquely sampled LIDAR data set designed to refine measurements of above ground carbon storage. Our new project quantitatively examines these data for evidence for past human activity. Preliminary results offer a promising path for tightly integrating archaeology, natural science, remote sensing and modeling for studying CNH dynamics in the deep and recent past.

Rural poverty and environmental degradation in the Philippines: A system dynamics approach

NASA Astrophysics Data System (ADS)

Parayno, Phares Penuliar

Poverty among the small cultivators in the Philippines remains widespread despite a general increase in per capita income during the last three decades. At the same time, the degradation of agricultural land resources, as sources of daily subsistence for the rural workers, is progressing. Past policy studies on the alleviation of rural poverty in the developing countries have centered on the issue of increasing food production and expanding economic growth but gave little attention to the issue of constraints imposed by degradation of agricultural land resources. Only in recent years have there been increasing focus on the relationship between rural poverty and environmental degradation. Inquiry is, however, often done by simplistic one way causal relationships which, although often illuminating, does not provide a comprehensive understanding of the different interacting processes that create rural poverty and land degradation. Thus, policies ensuing from such analyses provide only short-term gains without effecting lasting improvement in the living conditions of the small cultivators. This dissertation examines the complex interrelationships between rural poverty and land degradation and attempts to explain the inefficacy of broad development programs implemented in alleviating rural poverty and reversing deterioration of land resources. The study uses the case of the Philippines for empirical validation. The analysis employs computer simulation experiments with a system dynamics model of a developing economy consisting of an agricultural sector whose microstructure incorporates processes influencing: agricultural production; disbursement of income; changes in the quality of agricultural land resources; demographic behavior; and rural-urban transfer of real and monetary resources. The system dynamics model used in this study extends the wage and income distribution model of Saeed (1988) by adding to it decision structures concerning changes in the quality of agricultural land resources and rural-urban interaction. The study concludes that development programs advancing growth in agricultural production and providing technological, organizational, and financial assistance to target poor groups would not deliver long-term improvement in the economic conditions of the poor peasants unless distribution of land is altered. Similarly, policies promoting land improvement and conservation measures in an economic environment where land ownership remains skewed do not produce lasting betterment of agricultural land quality. It has been shown that a policy, which discourages the separation of land ownership from cultivatorship by imposing a tax on income accrued from absentee ownership, is therefore very critical in promoting land ownership among small cultivators and changing unequal land and income distribution. However, in order to sustain the improvement in the economic and environmental conditions of the small cultivators, this policy of taxing rent income must be complemented by policies that: (1) promote increases in agricultural production; (2) provide technological, organizational, and financial assistance to the small farmers; and (3) promote land improvement measures.

The importance of land cover change across urban-rural typologies for climate modeling.

PubMed

Vargo, Jason; Habeeb, Dana; Stone, Brian

2013-01-15

Land cover changes affect local surface energy balances by changing the amount of solar energy reflected, the magnitude and duration over which absorbed energy is released as heat, and the amount of energy that is diverted to non-heating fluxes through evaporation. However, such local influences often are only crudely included in climate modeling exercises, if at all. A better understanding of local land conversion dynamics can serve to inform inputs for climate models and increase the role for land use planning in climate management policy. Here we present a new approach for projecting and incorporating metropolitan land cover change into mesoscale climate and other environmental assessment models. Our results demonstrate the relative contributions of different land development patterns to land cover change and conversion and suggest that regional growth management strategies serving to increase settlement densities over time can have a significant influence on the rate of deforestation per unit of population growth. Employing the approach presented herein, the impacts of land conversion on climate change and on parallel environmental systems and services, such as ground water recharge, habitat provision, and food production, may all be investigated more closely and managed through land use planning. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dynamic Mesoscale Land-Atmosphere Feedbacks in Fragmented Forests in Amazonia

NASA Astrophysics Data System (ADS)

Rastogi, D.; Baidya Roy, S.

2011-12-01

This paper investigates land-atmosphere feedbacks in disturbed rainforests of Amazonia. Deforestation along the rapidly expanding highways and road network has created the unique fishbone land cover pattern in Rondonia, a state in southwestern Amazonia. Numerical experiments and observations show that sharp gradients in land cover due to the fishbone heterogeneity triggers mesoscale circulations. These circulations significantly change the spatial pattern of local hydrometeorology, especially convection, clouds and precipitation. The primary research question now is can these changes in local hydrometeorology affect vegetation growth in the clearings. If so, that would be a clear indication that land-atmosphere feedbacks can affect vegetation recovery in fragmented forests. A computationally-efficient modeling tool consisting of a mesoscale atmospheric model dynamically coupled with a plant growth model has been specifically developed to identify the atmospheric feedback pathways. Preliminary experiments focus on the seasonal-scale feedbacks during the dry season. Results show that temperature, incoming shortwave and precipitation are the three primary drivers through which the feedbacks operate. Increasing temperature increases respiratory losses generating a positive feedback. Increased cloud cover reduces incoming PAR and photosynthesis, resulting in a positive feedback. Increased precipitation reduces water stress and promotes growth resulting in a negative feedback. The net effect is a combination of these 3 feedback loops. These findings can significantly improve our understanding of ecosystem resiliency in disturbed tropical forests.

Forest and Agricultural Sector Optimization Model Greenhouse Gas Version (FASOM-GHG)

EPA Science Inventory

FASOM-GHG is a dynamic, multi-period, intertemporal, price-endogenous, mathematical programming model depicting land transfers and other resource allocations between and within the agricultural and forest sectors in the US. The model solution portrays simultaneous market equilibr...

Role of collisions in erosion of regolith during a lunar landing.

PubMed

Berger, Kyle J; Anand, Anshu; Metzger, Philip T; Hrenya, Christine M

2013-02-01

The supersonic gas plume of a landing rocket entrains lunar regolith, which is the layer of loose solids covering the lunar surface. This ejection is problematic due to scouring and dust impregnation of surrounding hardware, reduction in visibility for the crew, and spoofing of the landing sensors. To date, model predictions of erosion and ejection dynamics have been based largely on single-trajectory models in which the role of interparticle collisions is ignored. In the present work, the parameters affecting the erosion rate of monodisperse solids are investigated using the discrete element method (DEM). The drag and lift forces exerted by the rocket exhaust are incorporated via one-way coupling. The results demonstrate that interparticle collisions are frequent in the region immediately above the regolith surface; as many as 20% of particles are engaged in a collision at a given time. These collisions play an important role both in the erosion dynamics and in the final trajectories of particles. In addition, a direct assessment of the influence of collisions on the erosion rate is accomplished via a comparison between a "collisionless" DEM model and the original DEM model. This comparison shows that the erosion dynamics change drastically when collisions are considered and that the erosion rate is dependent on the collision parameters (coefficient of restitution and coefficient of friction). Physical explanations for these trends are provided.

Quantifying Grassland-to-Woodland Transitions and the Implications for Carbon and Nitrogen Dynamics in the Southwest United States

NASA Technical Reports Server (NTRS)

Wessman, Carol A.; Archer, Steven R.; Asner, Gregory P.; Bateson, C. Ann

2004-01-01

Replacement of grasslands and savannas by shrublands and woodlands has been widely reported in tropical, temperate and high-latitude rangelands worldwide (Archer 1994). These changes in vegetation structure may reflect historical shifts in climate and land use; and are likely to influence biodiversity, productivity, above- and below ground carbon and nitrogen sequestration and biophysical aspects of land surface-atmosphere interactions. The goal of our proposed research is to investigate how changes in the relative abundance of herbaceous and woody vegetation affect carbon and nitrogen dynamics across heterogeneous savannas and shrub/woodlands. By linking actual land-cover composition (derived through spectral mixture analysis of AVIRIS, TM, and AVHRR imagery) with a process-based ecosystem model, we will generate explicit predictions of the C and N storage in plants and soils resulting from changes in vegetation structure. Our specific objectives will be to (1) continue development and test applications of spectral mixture analysis across grassland-to-woodland transitions; (2) quantify temporal changes in plant and soil C and N storage and turnover for remote sensing and process model parameterization and verification; and (3) couple landscape fraction maps to an ecosystem simulation model to observe biogeochemical dynamics under changing landscape structure and climatological forcings.

The impact of anthropogenic land use and land cover change on regional climate extremes.

PubMed

Findell, Kirsten L; Berg, Alexis; Gentine, Pierre; Krasting, John P; Lintner, Benjamin R; Malyshev, Sergey; Santanello, Joseph A; Shevliakova, Elena

2017-10-20

Land surface processes modulate the severity of heat waves, droughts, and other extreme events. However, models show contrasting effects of land surface changes on extreme temperatures. Here, we use an earth system model from the Geophysical Fluid Dynamics Laboratory to investigate regional impacts of land use and land cover change on combined extremes of temperature and humidity, namely aridity and moist enthalpy, quantities central to human physiological experience of near-surface climate. The model's near-surface temperature response to deforestation is consistent with recent observations, and conversion of mid-latitude natural forests to cropland and pastures is accompanied by an increase in the occurrence of hot-dry summers from once-in-a-decade to every 2-3 years. In the tropics, long time-scale oceanic variability precludes determination of how much of a small, but significant, increase in moist enthalpy throughout the year stems from the model's novel representation of historical patterns of wood harvesting, shifting cultivation, and regrowth of secondary vegetation and how much is forced by internal variability within the tropical oceans.

Towards a more efficient and robust representation of subsurface hydrological processes in Earth System Models

NASA Astrophysics Data System (ADS)

Rosolem, R.; Rahman, M.; Kollet, S. J.; Wagener, T.

2017-12-01

Understanding the impacts of land cover and climate changes on terrestrial hydrometeorology is important across a range of spatial and temporal scales. Earth System Models (ESMs) provide a robust platform for evaluating these impacts. However, current ESMs lack the representation of key hydrological processes (e.g., preferential water flow, and direct interactions with aquifers) in general. The typical "free drainage" conceptualization of land models can misrepresent the magnitude of those interactions, consequently affecting the exchange of energy and water at the surface as well as estimates of groundwater recharge. Recent studies show the benefits of explicitly simulating the interactions between subsurface and surface processes in similar models. However, such parameterizations are often computationally demanding resulting in limited application for large/global-scale studies. Here, we take a different approach in developing a novel parameterization for groundwater dynamics. Instead of directly adding another complex process to an established land model, we examine a set of comprehensive experimental scenarios using a very robust and establish three-dimensional hydrological model to develop a simpler parameterization that represents the aquifer to land surface interactions. The main goal of our developed parameterization is to simultaneously maximize the computational gain (i.e., "efficiency") while minimizing simulation errors in comparison to the full 3D model (i.e., "robustness") to allow for easy implementation in ESMs globally. Our study focuses primarily on understanding both the dynamics for groundwater recharge and discharge, respectively. Preliminary results show that our proposed approach significantly reduced the computational demand while model deviations from the full 3D model are considered to be small for these processes.

Reconciling farming and wild nature: Integrating human-wildlife coexistence into the land-sharing and land-sparing framework.

PubMed

Crespin, Silvio J; Simonetti, Javier A

2018-05-11

Land has traditionally been spared to protect biodiversity; however, this approach has not succeeded by itself and requires a complementary strategy in human-dominated landscapes: land-sharing. Human-wildlife conflicts are rampant in a land-sharing context where wildlife co-occur with crops or livestock, but whose resulting interactions adversely affect the wellbeing of land owners, ultimately impeding coexistence. Therefore, true land-sharing only works if coexistence is also considered an end goal. We reviewed the literature on land-sharing and found that conflicts have not yet found their way into the land-sharing/sparing framework, with wildlife and humans co-occurring without coexisting in a dynamic process. To successfully implement a land-sharing approach, we must first acknowledge our failure to integrate the body of work on human-wildlife conflicts into the framework and work to implement multidisciplinary approaches from the ecological, economic, and sociological sciences to overcome and prevent conflicts. We suggest the use of Conflict Transformation by means of the Levels of Conflict Model to perceive both visible and deep-rooted causes of conflicts as opportunities to create problem-solving dynamics in affected socio-ecological landscapes. Reconciling farming and nature is possible by aiming for a transition to landscapes that truly share space by virtue of coexistence.

Comparison between remote sensing and a dynamic vegetation model for estimating terrestrial primary production of Africa.

PubMed

Ardö, Jonas

2015-12-01

Africa is an important part of the global carbon cycle. It is also a continent facing potential problems due to increasing resource demand in combination with climate change-induced changes in resource supply. Quantifying the pools and fluxes constituting the terrestrial African carbon cycle is a challenge, because of uncertainties in meteorological driver data, lack of validation data, and potentially uncertain representation of important processes in major ecosystems. In this paper, terrestrial primary production estimates derived from remote sensing and a dynamic vegetation model are compared and quantified for major African land cover types. Continental gross primary production estimates derived from remote sensing were higher than corresponding estimates derived from a dynamic vegetation model. However, estimates of continental net primary production from remote sensing were lower than corresponding estimates from the dynamic vegetation model. Variation was found among land cover classes, and the largest differences in gross primary production were found in the evergreen broadleaf forest. Average carbon use efficiency (NPP/GPP) was 0.58 for the vegetation model and 0.46 for the remote sensing method. Validation versus in situ data of aboveground net primary production revealed significant positive relationships for both methods. A combination of the remote sensing method with the dynamic vegetation model did not strongly affect this relationship. Observed significant differences in estimated vegetation productivity may have several causes, including model design and temperature sensitivity. Differences in carbon use efficiency reflect underlying model assumptions. Integrating the realistic process representation of dynamic vegetation models with the high resolution observational strength of remote sensing may support realistic estimation of components of the carbon cycle and enhance resource monitoring, providing suitable validation data is available.

Advances in Estimating Current and Future Effects of Climate and Management on Forest Ecosystem Carbon and Water Dynamics at Multiple Scales

NASA Astrophysics Data System (ADS)

Law, B. E.; Still, C. J.; Hudiburg, T. W.; Buotte, P.; Hanson, C. V.

2017-12-01

As we examine the integrated effects of climate variability, atmospheric CO2, and land management actions on terrestrial carbon and water processes within regions, and evaluate mitigation and adaptation options, we want our analysis to be as accurate as possible to reduce the risk of negative impacts from management decisions. The use of global land models at regional scales requires modifications for realistic projections. Model evaluation reveals knowledge and data gaps in species sensitivities to climate extremes and responses to land use change and management actions such as restoration. For example, a combination of sapflux and AmeriFlux tower measurements identifies seasonal shifts in the proportion of water vapor exchange that is due to tree transpiration, as well as changes in tree water-use efficiency associated with climate variation. Thermal measurements from an unmanned aerial system quantify canopy temperatures reached during extreme heat events, as well as tree-to-tree thermal variations, which can be related to transpiration dynamics. Diagnosis of land model performance across climate/vegetation gradients includes the combination of atmospheric CO2/CO/H2O observations from aircraft, a tall tower network, and a mobile platform, combined with inverse modeling. This approach identified an ecoregion where the Community Land Model (CLM4.5) underestimated net ecosystem production by 28%, suggesting model challenges in high productivity forests with high soil nitrogen and deep organic soils. We use land-model output of net ecosystem production, harvest and fire emissions to estimate net ecosystem carbon balance, which is input to a Life-Cycle Assessment of wood product use to estimate net carbon emissions to the atmosphere for harvest scenarios and bioenergy production. Such robust and interdisciplinary approaches are needed to more accurately quantify impacts on ecosystems and "what the atmosphere sees" in terms of greenhouse gas sources and impacts on ecosystems across landscapes and regions.

A simple hydrologically based model of land surface water and energy fluxes for general circulation models

NASA Technical Reports Server (NTRS)

Liang, XU; Lettenmaier, Dennis P.; Wood, Eric F.; Burges, Stephen J.

1994-01-01

A generalization of the single soil layer variable infiltration capacity (VIC) land surface hydrological model previously implemented in the Geophysical Fluid Dynamics Laboratory (GFDL) general circulation model (GCM) is described. The new model is comprised of a two-layer characterization of the soil column, and uses an aerodynamic representation of the latent and sensible heat fluxes at the land surface. The infiltration algorithm for the upper layer is essentially the same as for the single layer VIC model, while the lower layer drainage formulation is of the form previously implemented in the Max-Planck-Institut GCM. The model partitions the area of interest (e.g., grid cell) into multiple land surface cover types; for each land cover type the fraction of roots in the upper and lower zone is specified. Evapotranspiration consists of three components: canopy evaporation, evaporation from bare soils, and transpiration, which is represented using a canopy and architectural resistance formulation. Once the latent heat flux has been computed, the surface energy balance is iterated to solve for the land surface temperature at each time step. The model was tested using long-term hydrologic and climatological data for Kings Creek, Kansas to estimate and validate the hydrological parameters, and surface flux data from three First International Satellite Land Surface Climatology Project Field Experiment (FIFE) intensive field campaigns in the summer-fall of 1987 to validate the surface energy fluxes.

Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Yin, Runsheng; Li, Zhengpeng; Deng, Yulin; Tan, Kun; Deng, Xiangzheng; Rothstein, David; Qi, Jiaguo; Yin, Runsheng

2009-01-01

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon storage and loss. Here we use the General Ensemble Biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China's upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sinks/source pattern showed a high degree of spatial heterogeneity, Carbon sinks were associated with forest areas without disturbances, whereas carbon Sources were primarily caused by stand-replacing disturbances. This highlights the importance of land-use history in determining the regional carbon sinks/source pattern.

Meteorological Effects of Land Cover Changes in Hungary during the 20th Century

NASA Astrophysics Data System (ADS)

Drüszler, Á.; Vig, P.; Csirmaz, K.

2012-04-01

Geological, paleontological and geomorphologic studies show that the Earth's climate has always been changing since it came into existence. The climate change itself is self-evident. Therefore the far more serious question is how much does mankind strengthen or weaken these changes beyond the natural fluctuation and changes of climate. The aim of the present study was to restore the historical land cover changes and to simulate the meteorological consequences of these changes. Two different land cover maps for Hungary were created in vector data format using GIS technology. The land cover map for 1900 was reconstructed based on statistical data and two different historical maps: the derived map of the 3rd Military Mapping Survey of the Austro-Hungarian Empire and the Synoptic Forestry Map of the Kingdom of Hungary. The land cover map for 2000 was derived from the CORINE land cover database. Significant land cover changes were found in Hungary during the 20th century according to the examinations of these maps and statistical databases. The MM5 non-hydrostatic dynamic model was used to further evaluate the meteorological effects of these changes. The lower boundary conditions for this mesoscale model were generated for two selected time periods (for 1900 and 2000) based on the reconstructed maps. The dynamic model has been run with the same detailed meteorological conditions of selected days from 2006 and 2007, but with modified lower boundary conditions. The set of the 26 selected initial conditions represents the whole set of the macrosynoptic situations for Hungary. In this way, 2×26 "forecasts" were made with 48 hours of integration. The effects of land cover changes under different weather situations were further weighted by the long-term (1961-1990) mean frequency of the corresponding macrosynoptic types, to assume the climatic effects from these stratified averages. The detailed evaluation of the model results were made for three different meteorological variables (temperature, dew point and precipitation).

Advancing coupled human-earth system models: The integrated Earth System Model Project

NASA Astrophysics Data System (ADS)

Thomson, A. M.; Edmonds, J. A.; Collins, W.; Thornton, P. E.; Hurtt, G. C.; Janetos, A. C.; Jones, A.; Mao, J.; Chini, L. P.; Calvin, K. V.; Bond-Lamberty, B. P.; Shi, X.

2012-12-01

As human and biogeophysical models develop, opportunities for connections between them evolve and can be used to advance our understanding of human-earth systems interaction in the context of a changing climate. One such integration is taking place with the Community Earth System Model (CESM) and the Global Change Assessment Model (GCAM). A multi-disciplinary, multi-institution team has succeeded in integrating the GCAM integrated assessment model of human activity into CESM to dynamically represent the feedbacks between changing climate and human decision making, in the context of greenhouse gas mitigation policies. The first applications of this capability have focused on the feedbacks between climate change impacts on terrestrial ecosystem productivity and human decisions affecting future land use change, which are in turn connected to human decisions about energy systems and bioenergy production. These experiments have been conducted in the context of the RCP4.5 scenario, one of four pathways of future radiative forcing being used in CMIP5, which constrains future human-induced greenhouse gas emissions from energy and land activities to stabilize radiative forcing at 4.5 W/m2 (~650 ppm CO2 -eq) by 2100. When this pathway is run in GCAM with the climate feedback on terrestrial productivity from CESM, there are implications for both the land use and energy system changes required for stabilization. Early findings indicate that traditional definitions of radiative forcing used in scenario development are missing a critical component of the biogeophysical consequences of land use change and their contribution to effective radiative forcing. Initial full coupling of the two global models has important implications for how climate impacts on terrestrial ecosystems changes the dynamics of future land use change for agriculture and forestry, particularly in the context of a climate mitigation policy designed to reduce emissions from land use as well as energy systems. While these initial experiments have relied on offline coupling methodologies, current and future experiments are utilizing a single model code developed to integrate GCAM into CESM as a component of the land model. This unique capability facilitates many new applications to scientific questions arising from human and biogeophysical systems interaction. Future developments will further integrate the energy system decisions and greenhouse gas emissions as simulated in GCAM with the appropriate climate and land system components of CESM.

The Development in modeling Tibetan Plateau Land/Climate Interaction

NASA Astrophysics Data System (ADS)

Xue, Yongkang; Liu, Ye; li, qian; Maheswor Shrestha, Maheswor; Ma, Hsi-Yen; Cox, Peter; Sun, shufen; Koike, Toshio

2015-04-01

Tibetan Plateau (TP) plays an important role in influencing the continental and planetary scale climate, including East Asian and South Asian monsoon, circulation and precipitation over West Pacific and Indian Oceans. The numerical study has identified TP as the area with strongest land/atmosphere interactions over the midlatitude land. The land degradation there has also affected the monsoon precipitation in TP along the monsoon pathway. The water cycle there affects water sources for major Asian river systems, which include the Tarim, Amu Darya, Indus, Ganges, Brahmaputra, Irrawaddy, Salween, Mekong, Yellow, and Yangtze Rivers. Despite the importance of TP land process in the climate system, the TP land surface processes are poorly modeled due to lack of data available for model validation. To better understand, simulate, and project the role of Tibetan Plateau land surface processes, better parameterization of the Tibetan Land surface processes have been developed and evaluated. The recently available field measurement there and satellite observation have greatly helped this development. This paper presents these new developments and preliminary results using the newly developed biophysical/dynamic vegetation model, frozen soil model, and glacier model. In recent CMIP5 simulation, the CMIP5 models with dynamic vegetation model show poor performance in simulating the TP vegetation and climate. To better simulate the TP vegetation condition and its interaction with climate, we have developed biophysical/dynamic vegetation model, the Simplified Simple Biosphere Model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID), based on water, carbon, and energy balance. The simulated vegetation variables are updates, driven by carbon assimilation, allocation, and accumulation, as well as competition between plant functional types. The model has been validated with the station data, including those measured over the TP. The offline SSiB4/TRIFFID is integrated using the observed precipitation and reanalysis-based meteorological forcing from 1948 to 2008 with 1 degree horizontal resolution. The simulated vegetation conditions and surface hydrology are compared well with observational data with some bias, and shows strong decadal and interannual variabilities with a linear trend associated with the global warming. The TP region is covered by both discontinuous and sporadic permafrost with irregular snow layers above. A frozen soil model is developed to take the coupling effect of mass and heat transport into consideration and includes a detailed description of mass balances of volumetric liquid water, ice, as well as vapor content. It also considers contributions' of heat conduction to the energy balance. The model has been extensively tested using a number of TP station data, which included soil temperature and soil water measurements. The results suggest that it is important to include the frozen sol process to adequately simulate the surface energy balance during the freezing and thawing periods and surface temperature variability, including its diurnal variation. Issues in simulating permafrost process will also be addressed. To better understand the glacier variations under climate change scenarios, an integrated modeling system with an energy budget-based multilayer scheme for clean glaciers, a single-layer scheme for debris-covered glaciers and multilayer scheme for seasonal snow over glacier, soil and forest are developed within a distributed biosphere hydrological modeling framework (WEB-DHM-S model). Discharge simulations using this model show good agreement with observations for Hunza River Basin (13,733 km2) in the Karakoram region of Pakistan for three hydrologic years (2002-2004). Flow composition analysis reveals that the runoff regime is strongly controlled by the snow and glacier melt runoff (50% snowmelt and 33% glacier melt) and suggests that both topography and glacier hypsometry play key roles in glacier mass balance. This study provides a basis for potential application of such an integrated model to the entire Hindu-Kush-Karakoram-Himalaya region.

Space-based Ornithology-Studying Bird Migration and Environmental Change in North America

NASA Technical Reports Server (NTRS)

Smith, James; Deppe, Jill

2008-01-01

Natural fluctuations in the availability of critical stopover sites coupled with anthropogenic destruction of wetlands, land-use change, and anticipated losses due to climate change present migratory birds with a formidable challenge. We have developed an individual-based, spatially explicit bird migration model that simulates the migration routes, timing and energy budgets of individual birds under dynamic weather and land surface conditions. Our model incorporates biophysical constraints, individual bird energy status, bird behavior, and flight aerodynamics. We model the speed, direction, and timing of individual birds moving through a user specified Lagrangian grid. The model incorporates environmental properties including wind speed and direction, topography, dynamic hydrologic properties of the landscape, and environmental suitability. The model is driven by important variables estimated from satellite observations of the land surface, by data assimilation products from weather and climate models, and biological field data. We illustrate the use of the model to study the impact of both short- and long-term environmental variatios, e.g. climate, drought, anthropogenic, on migration timing (phenology), spatial pattern, and fitness (survival and reproductive success). We present several theoretical simulations of the spring migration of Pectoral Sandpiper (Calidris melanotos) in North America with emphasis on the Central flyway from the Gulf of Mexico to Alaska.

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.

Rough-water Landings of a 0.1-Size Powered Dynamic Model of the XP5Y-1 Flying Boat with Two Types of Afterbody - Langley Tank Model 228 (TED No. NACA DE309)

NASA Technical Reports Server (NTRS)

Garrison, Charlie C.

1949-01-01

A 0.1-size powered dynamic model of a large, high-speed flying boat was landed in Langley tank no. 1 into oncoming waves 4 feet high (full size). The model was tested with two afterbodies of differing lengths (4.12 and 6.63 beams). The short afterbody had a constant angle of dead rise of 22.5deg and a keel angle of 6.5deg. The long afterbody had warped dead rise and a keel angle of 8.5deg. The vertical accelerations were slightly greater and the maximum angular accelerations and maxim= trims were slightly less for the model with the long afterbody than for the model with -the short afterbody. A wave length of 210 feet (full size) imposed the highest accelerations on the model with either the long or the short afterbody.

Dynamic effects of root system architecture improve root water uptake in 1-D process-based soil-root hydrodynamics

NASA Astrophysics Data System (ADS)

Bouda, Martin; Saiers, James E.

2017-12-01

Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, descriptions of RSA have not been included because of their three-dimensional complexity, which makes them generally too computationally costly. Here we demonstrate a new, process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA under different soil moisture conditions: the RSA stencil. Using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, we show that the RSA stencil predicts plant water potentials within 2% to the outputs of a full 3D model, under the same assumptions on soil moisture heterogeneity, despite its trivial computational cost, resulting in improved predictions of water uptake and soil moisture compared to a model without RSA in a transient simulation. Our results suggest that LSM predictions of soil moisture dynamics and dependent variables can be improved by the implementation of this model, calibrated for individual PFTs using field observations.

Soil Water Balance and Vegetation Dynamics in two Water-limited Mediterranean Ecosystem on Sardinia under past and future climate change

NASA Astrophysics Data System (ADS)

Corona, R.; Montaldo, N.; Albertson, J. D.

2016-12-01

Water limited conditions strongly impacts soil and vegetation dynamics in Mediterranean regions, which are commonly heterogeneous ecosystems, characterized by inter-annual rainfall variability, topography variability and contrasting plant functional types (PFTs) competing for water use. Historical human influences (e.g., deforestation, urbanization) further altered these ecosystems. Sardinia island is a representative region of Mediterranean ecosystems. It is low urbanized except some plan areas close to the main cities where main agricultural activities are concentrated. Two contrasting case study sites are within the Flumendosa river basin (1700 km2). The first site is a typical grassland on an alluvial plan valley (soil depth > 2m) while the second is a patchy mixture of Mediterranean vegetation species (mainly wild olive trees and C3 herbaceous) that grow in a soil bounded from below by a rocky layer of basalt, partially fractured (soil depth 15 - 40 cm). In both sites land-surface fluxes and CO2 fluxes are estimated by the eddy correlation technique while soil moisture was continuously estimated with water content reflectometers, and periodically leaf area index (LAI) was estimated. The following objectives are addressed:1) pointing out the dynamics of land surface fluxes, soil moisture, CO2 and vegetation cover for two contrasting water-limited ecosystems; 2) assess the impact of the soil depth and type on the CO2 and water balance dynamics; 3) evaluate the impact of past and future climate change scenarios on the two contrasting ecosystems. For reaching the objectives an ecohydrologic model that couples a vegetation dynamic model (VDM), and a 3-component (bare soil, grass and woody vegetation) land surface model (LSM) has been used. Historical meteorological data are available from 1922 and hydro-meteorological scenarios are then generated using a weather generator. The VDM-LSM model predict soil water balance and vegetation dynamics for the generated hydrometeorological scenarios in the two contrasting ecosystems. Results demonstrate that vegetation dynamics are influenced by the inter-annual variability of atmospheric forcing, with vegetation density changing significantly according to seasonal rainfall amount. At the same time the vegetation dynamics affect the soil water balance.

Effects of harvest on carbon and nitrogen dynamics in a Pacific Northwest forest catchment

Treesearch

Alex Abdelnour; Robert B. McKane; Marc Stieglitz; Feifei Pan; Yiwei Cheng

2013-01-01

We used a new ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA), to analyze the effects of forest harvest on catchment carbon and nitrogen dynamics. We applied the model to a 10 ha headwater catchment in the western Oregon Cascade Range where two major disturbance events have occurred during the past 500 years: a stand-replacing fire...

The land-use legacy effect: Towards a mechanistic understanding of time-lagged water quality responses to land use/cover.

PubMed

Martin, Sherry L; Hayes, Daniel B; Kendall, Anthony D; Hyndman, David W

2017-02-01

Numerous studies have linked land use/land cover (LULC) to aquatic ecosystem responses, however only a few have included the dynamics of changing LULC in their analysis. In this study, we explicitly recognize changing LULC by linking mechanistic groundwater flow and travel time models to a historical time series of LULC, creating a land-use legacy map. We then illustrate the utility of legacy maps to explore relationships between dynamic LULC and lake water chemistry. We tested two main concepts about mechanisms linking LULC and lake water chemistry: groundwater pathways are an important mechanism driving legacy effects; and, LULC over multiple spatial scales is more closely related to lake chemistry than LULC over a single spatial scale. We applied statistical models to twelve water chemistry variables, ranging from nutrients to relatively conservative ions, to better understand the roles of biogeochemical reactivity and solubility on connections between LULC and aquatic ecosystem response. Our study illustrates how different areas can have long groundwater pathways that represent different LULC than what can be seen on the landscape today. These groundwater pathways delay the arrival of nutrients and other water quality constituents, thus creating a legacy of historic land uses that eventually reaches surface water. We find that: 1) several water chemistry variables are best fit by legacy LULC while others have a stronger link to current LULC, and 2) single spatial scales of LULC analysis performed worse for most variables. Our novel combination of temporal and spatial scales was the best overall model fit for most variables, including SRP where this model explained 54% of the variation. We show that it is important to explicitly account for temporal and spatial context when linking LULC to ecosystem response. Copyright © 2016. Published by Elsevier B.V.

Transient dynamics of terrestrial carbon storage: Mathematical foundation and its applications

DOE PAGES

Luo, Yiqi; Shi, Zheng; Lu, Xingjie; ...

2017-01-12

Terrestrial ecosystems have absorbed roughly 30% of anthropogenic CO 2 emissions over the past decades, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling and experimental and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under global change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g.,more » net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, which is the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3-D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. In addition, the physical emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. Altogether, this new mathematical framework offers new approaches to understanding, evaluating, diagnosing, and improving land C cycle models.« less

Transient dynamics of terrestrial carbon storage: Mathematical foundation and its applications

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

Luo, Yiqi; Shi, Zheng; Lu, Xingjie

Terrestrial ecosystems have absorbed roughly 30% of anthropogenic CO 2 emissions over the past decades, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling and experimental and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under global change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g.,more » net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, which is the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3-D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. In addition, the physical emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. Altogether, this new mathematical framework offers new approaches to understanding, evaluating, diagnosing, and improving land C cycle models.« less

Design optimization of aircraft landing gear assembly under dynamic loading

NASA Astrophysics Data System (ADS)

Wong, Jonathan Y. B.

As development cycles and prototyping iterations begin to decrease in the aerospace industry, it is important to develop and improve practical methodologies to meet all design metrics. This research presents an efficient methodology that applies high-fidelity multi-disciplinary design optimization techniques to commercial landing gear assemblies, for weight reduction, cost savings, and structural performance dynamic loading. Specifically, a slave link subassembly was selected as the candidate to explore the feasibility of this methodology. The design optimization process utilized in this research was sectioned into three main stages: setup, optimization, and redesign. The first stage involved the creation and characterization of the models used throughout this research. The slave link assembly was modelled with a simplified landing gear test, replicating the behavior of the physical system. Through extensive review of the literature and collaboration with Safran Landing Systems, dynamic and structural behavior for the system were characterized and defined mathematically. Once defined, the characterized behaviors for the slave link assembly were then used to conduct a Multi-Body Dynamic (MBD) analysis to determine the dynamic and structural response of the system. These responses were then utilized in a topology optimization through the use of the Equivalent Static Load Method (ESLM). The results of the optimization were interpreted and later used to generate improved designs in terms of weight, cost, and structural performance under dynamic loading in stage three. The optimized designs were then validated using the model created for the MBD analysis of the baseline design. The design generation process employed two different approaches for post-processing the topology results produced. The first approach implemented a close replication of the topology results, resulting in a design with an overall peak stress increase of 74%, weight savings of 67%, and no apparent cost savings due to complex features present in the design. The second design approach focused on realizing reciprocating benefits for cost and weight savings. As a result, this design was able to achieve an overall peak stress increase of 6%, weight and cost savings of 36%, and 60%, respectively.

Exploring Land Use and Land Cover Change and Feedbacks in the Global Change Assessment Model

NASA Astrophysics Data System (ADS)

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

2017-12-01

Land Use and Land Cover Change (LULCC) is a major driver of global and regional environmental change. Projections of land use change are thus an essential component in Integrated Assessment Models (IAMs) to study feedbacks between transformation of energy systems and land productivity under the context of climate change. However, the spatial scale of IAMs, e.g., the Global Change Assessment Model (GCAM), is typically larger than the scale of terrestrial processes in the human-Earth system, LULCC downscaling therefore becomes a critical linkage among these multi-scale and multi-sector processes. Parametric uncertainties in LULCC downscaling algorithms, however, have been under explored, especially in the context of how such uncertainties could propagate to affect energy systems in a changing climate. In this study, we use a LULCC downscaling model, Demeter, to downscale GCAM-based future land use scenarios into fine spatial scales, and explore the sensitivity of downscaled land allocations to key parameters. Land productivity estimates (e.g., biomass production and crop yield) based on the downscaled LULCC scenarios are then fed to GCAM to evaluate how energy systems might change due to altered water and carbon cycle dynamics and their interactions with the human system, , which would in turn affect future land use projections. We demonstrate that uncertainties in LULCC downscaling can result in significant differences in simulated scenarios, indicating the importance of quantifying parametric uncertainties in LULCC downscaling models for integrated assessment studies.

Assessing Northern Hemisphere Land-Atmosphere Hotspots Using Dynamical Adjustment

NASA Astrophysics Data System (ADS)

Merrifield, Anna; Lehner, Flavio; Deser, Clara; Xie, Shang-Ping

2017-04-01

Understanding the influence of soil moisture on surface air temperature (SAT) is made more challenging by large-scale, internal atmospheric variability present in the midlatitude summer atmosphere. In this study, dynamical adjustment is used to characterize and remove summer SAT variability associated with large-scale circulation patterns in the Community Earth System Model large ensemble (CESM-LE). The adjustment is performed over North America and Europe with two different circulation indicators: sea level pressure (SLP) and 500mb height (Z500). The removal of dynamical "noise" leaves residual SAT variability in the central U.S. and Mediterranean regions identified as hotspots of land-atmosphere interaction (e.g. Koster et al. 2004, Seneviratne et al. 2006). The residual SAT variability "signal" is not clearly related to modes of sea surface temperature (SST) variability, but is related to local soil moisture, evaporative fraction, and radiation availability. These local relationships suggest that residual SAT variability is representative of the aggregate land surface signal. SLP dynamical adjustment removes ˜15% more variability in the central U.S. hotspot region than Z500 dynamical adjustment. Similar amounts of variability are removed by SLP and Z500 in the Mediterranean region. Differences in SLP and Z500 signal magnitude in the central U.S. are likely due to the modification of SLP by local land surface conditions, while the proximity of European hotspots to the Mediterranean sea mitigates the land surface influence. Variations in the Z500 field more closely resemble large-scale midlatitude circulation patterns and therefore Z500 may be a more suitable circulation indicator for summer dynamical adjustment. Changes in the residual SAT variability signal under increased greenhouse gas forcing will also be explored.

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.

Analysis of economic values of land use and land cover changes in crisis territories by satellite data: models of socio-economy and population dynamics in war

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy V.; Yuschenko, Maxim; Movchan, Dmytro; Kopachevsky, Ivan

2017-10-01

Problem of remote sensing data harnessing for decision making in conflict territories is considered. Approach for analysis of socio-economic and demographic parameters with a limited set of data and deep uncertainty is described. Number of interlinked techniques to estimate a population and economy in crisis territories are proposed. Stochastic method to assessment of population dynamics using multi-source data using remote sensing data is proposed. Adaptive Markov's chain based method to study of land-use changes using satellite data is proposed. Proposed approach is applied to analysis of socio-economic situation in Donbas (East Ukraine) territory of conflict in 2014-2015. Land-use and landcover patterns for different periods were analyzed using the Landsat and MODIS data . The land-use classification scheme includes the following categories: (1) urban or built-up land, (2) barren land, (3) cropland, (4) horticulture farms, (5) livestock farms, (6) forest, and (7) water. It was demonstrated, that during the period 2014-2015 was not detected drastic changes in land-use structure of study area. Heterogeneously distributed decreasing of horticulture farms (4-6%), livestock farms (5-6%), croplands (3-4%), and increasing of barren land (6-7%) have been observed. Way to analyze land-cover productivity variations using satellite data is proposed. Algorithm is based on analysis of time-series of NDVI and NDWI distributions. Drastic changes of crop area and its productivity were detected. Set of indirect indicators, such as night light intensity, is also considered. Using the approach proposed, using the data utilized, the local and regional GDP, local population, and its dynamics are estimated.

Measurement of in vivo anterior cruciate ligament strain during dynamic jump landing

PubMed Central

Taylor, K.A.; Terry, M.E.; Utturkar, G.M.; Spritzer, C.E.; Queen, R.M.; Irribarra, L.A.; Garrett, W.E.; DeFrate, L.E.

2011-01-01

Despite recent attention in the literature, anterior cruciate ligament (ACL) injury mechanisms are controversial and incidence rates remain high. One explanation is limited data on in vivo ACL strain during high-risk, dynamic movements. The objective of this study was to quantify ACL strain during jump landing. Marker-based motion analysis techniques were integrated with fluoroscopic and magnetic resonance (MR) imaging techniques to measure dynamic ACL strain non-invasively. First, eight subjects’ knees were imaged using MR. From these images, the cortical bone and ACL attachment sites of the tibia and femur were outlined to create 3D models. Subjects underwent motion analysis while jump landing using reflective markers placed directly on the skin around the knee. Next, biplanar fluoroscopic images were taken with the markers in place so that the relative positions of each marker to the underlying bone could be quantified. Numerical optimization allowed jumping kinematics to be superimposed on the knee model, thus reproducing the dynamic in vivo joint motion. ACL length, knee flexion, and ground reaction force were measured. During jump landing, average ACL strain peaked 55 ± 14 ms (mean and 95% confidence interval) prior to ground impact, when knee flexion angles were lowest. The peak ACL strain, measured relative to its length during MR imaging, was 12 ± 7%. The observed trends were consistent with previously described neuromuscular patterns. Unrestricted by field of view or low sampling rate, this novel approach provides a means to measure kinematic patterns that elevate ACL strains and that provide new insights into ACL injury mechanisms. PMID:21092960

Detection and assessment of land use dynamics on Tenerife (Canary Islands): the agricultural development between 1986 and 2010

NASA Astrophysics Data System (ADS)

Günthert, Sebastian; Naumann, Simone; Siegmund, Alexander

2012-10-01

Since Spanish colonial times, the Canary Islands and especially Tenerife have always been used for intensive agriculture. Today almost 1/4 of the total area of Tenerife are agriculturally affected, whereas especially mountainous areas with suitable climate conditions are drastically transformed for agricultural use by building of large terraces. In recent years, political and economical developments lead to a further transformation process, especially inducted by an expansive tourism, which caused concentration- and intensification-tendencies of agricultural land use in lower altitudes as well as agricultural set-aside and rural exodus in the hinterland. The overall aim of the research at hand is to address the agricultural land use dynamics of the past decades, to statistically assess the causal reasons for those changes and to model the future agricultural land use dynamics on Tenerife. Therefore, an object-based classification procedure for recent RapidEye data (2010), Spot 4 (1998) as well as SPOT 1 (1986-88) imagery was developed, followed by a post classification comparison (PCC). Older agricultural fallow land or agricultural set-aside with a higher level of natural succession can hardly be acquired in the used medium satellite imagery. Hence, a second detection technique was generated, which allows an exact identification of the total agriculturally affected area on Tenerife, also containing older agricultural fallow land or agricultural set-aside. The method consists of an automatic texture-oriented detection and area-wide extraction of linear agricultural structures (plough furrows and field boundaries of arable land, utilised and non-utilised agricultural terraces) in current orthophotos of Tenerife. Once the change detection analysis is realised, it is necessary to identify the different driving forces which are responsible for the agricultural land use dynamics. The statistical connections between agricultural land use changes and these driving forces are identified by the use of correlation and regression analyses.

76 FR 17332 - Special Conditions: Embraer S.A.; Model EMB 500; Single-Place Side-Facing Seat Dynamic Test...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-29

... locked open during taxi, takeoff and landing. The adjacent forward wall/bulkhead interior structure will... inches of energy absorbing protective padding (foam or equivalent), such as Ensolite. 3. Thoracic Trauma... occupied, the lavatory door must be latched open for takeoff and landing and must remain latched under the...

Local variability mediates vulnerability of trout populations to land use and climate change

Treesearch

Brooke E. Penaluna; Jason B. Dunham; Steve F. Railsback; Ivan Arismendi; Sherri L. Johnson; Robert E. Bilby; Mohammad Safeeq; Arne E. Skaugset; James P. Meador

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of...

Ecosystem management can mitigate vegetation shifts induced by climate change in African savannas

NASA Astrophysics Data System (ADS)

Scheiter, Simon; Savadogo, Patrice

2017-04-01

The welfare of people in the tropics and sub-tropics strongly depends on goods and services that ecosystems supply. Flows of these ecosystem services are strongly influenced by interactions between climate change and land use. A prominent example are savannas, covering approximately 20% of the Earth's land surface. Key ecosystem services in these areas are fuel wood for cooking and heating, food production and livestock. Changes in the structure and dynamics of savanna vegetation may strongly influence local people's living conditions, as well as the climate system and biogeochemical cycles. We used a dynamic vegetation model to explore interactive effects of climate and land use on the vegetation structure, distribution and carbon cycling of African savannas under current and future conditions. More specifically, we simulate long term impacts of fire management, grazing and fuel wood harvesting. The model projects that under future climate without human land use impacts, large savanna areas would shift towards more wood dominated vegetation due to CO2 fertilization effects and changes in water use efficiency. However, land use activities can mitigate climate change impacts on vegetation to maintain desired ecosystem states that ensure fluxes of important ecosystem services. We then use optimization algorithms to identify sustainable land use strategies that maximize the utility of people managing savannas while preserving a stable vegetation state. Our results highlight that the development of land use policy for tropical and sub-tropical areas needs to account for climate change impacts on vegetation.

14 CFR 25.562 - Emergency landing dynamic conditions.

Code of Federal Regulations, 2010 CFR

2010-01-01

....562 Emergency landing dynamic conditions. (a) The seat and restraint system in the airplane must be... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Emergency landing dynamic conditions. 25... successfully complete dynamic tests or be demonstrated by rational analysis based on dynamic tests of a similar...

14 CFR 27.562 - Emergency landing dynamic conditions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Emergency landing dynamic conditions. 27... Conditions § 27.562 Emergency landing dynamic conditions. (a) The rotorcraft, although it may be damaged in... must successfully complete dynamic tests or be demonstrated by rational analysis based on dynamic tests...

Land surface sensitivity of monsoon depressions formed over Bay of Bengal using improved high-resolution land state

NASA Astrophysics Data System (ADS)

Rajesh, P. V.; Pattnaik, S.; Mohanty, U. C.; Rai, D.; Baisya, H.; Pandey, P. C.

2017-12-01

Monsoon depressions (MDs) constitute a large fraction of the total rainfall during the Indian summer monsoon season. In this study, the impact of high-resolution land state is addressed by assessing the evolution of inland moving depressions formed over the Bay of Bengal using a mesoscale modeling system. Improved land state is generated using High Resolution Land Data Assimilation System employing Noah-MP land-surface model. Verification of soil moisture using Soil Moisture and Ocean Salinity (SMOS) and soil temperature using tower observations demonstrate promising results. Incorporating high-resolution land state yielded least root mean squared errors with higher correlation coefficient in the surface and mid tropospheric parameters. Rainfall forecasts reveal that simulations are spatially and quantitatively in accordance with observations and provide better skill scores. The improved land surface characteristics have brought about the realistic evolution of surface, mid-tropospheric parameters, vorticity and moist static energy that facilitates the accurate MDs dynamics in the model. Composite moisture budget analysis reveals that the surface evaporation is negligible compared to moisture flux convergence of water vapor, which supplies moisture into the MDs over land. The temporal relationship between rainfall and moisture convergence show high correlation, suggesting a realistic representation of land state help restructure the moisture inflow into the system through rainfall-moisture convergence feedback.

Simulation of Regionally Ecological Land Based on a Cellular Automation Model: A Case Study of Beijing, China

PubMed Central

Xie, Hualin; Kung, Chih-Chun; Zhang, Yanting; Li, Xiubin

2012-01-01

Ecological land is like the “liver” of a city and is very useful to public health. Ecological land change is a spatially dynamic non-linear process under the interaction between natural and anthropogenic factors at different scales. In this study, by setting up natural development scenario, object orientation scenario and ecosystem priority scenario, a Cellular Automation (CA) model has been established to simulate the evolution pattern of ecological land in Beijing in the year 2020. Under the natural development scenario, most of ecological land will be replaced by construction land and crop land. But under the scenarios of object orientation and ecosystem priority, the ecological land area will increase, especially under the scenario of ecosystem priority. When considering the factors such as total area of ecological land, loss of key ecological land and spatial patterns of land use, the scenarios from priority to inferiority are ecosystem priority, object orientation and natural development, so future land management policies in Beijing should be focused on conversion of cropland to forest, wetland protection and prohibition of exploitation of natural protection zones, water source areas and forest parks to maintain the safety of the regional ecosystem. PMID:23066410

Simulation of regionally ecological land based on a cellular automation model: a case study of Beijing, China.

PubMed

Xie, Hualin; Kung, Chih-Chun; Zhang, Yanting; Li, Xiubin

2012-08-01

Ecological land is like the "liver" of a city and is very useful to public health. Ecological land change is a spatially dynamic non-linear process under the interaction between natural and anthropogenic factors at different scales. In this study, by setting up natural development scenario, object orientation scenario and ecosystem priority scenario, a Cellular Automation (CA) model has been established to simulate the evolution pattern of ecological land in Beijing in the year 2020. Under the natural development scenario, most of ecological land will be replaced by construction land and crop land. But under the scenarios of object orientation and ecosystem priority, the ecological land area will increase, especially under the scenario of ecosystem priority. When considering the factors such as total area of ecological land, loss of key ecological land and spatial patterns of land use, the scenarios from priority to inferiority are ecosystem priority, object orientation and natural development, so future land management policies in Beijing should be focused on conversion of cropland to forest, wetland protection and prohibition of exploitation of natural protection zones, water source areas and forest parks to maintain the safety of the regional ecosystem.

A Generalized Deforestation and Land-Use Change Scenario Generator for Use in Climate Modelling Studies

PubMed Central

Tompkins, Adrian Mark; Caporaso, Luca; Biondi, Riccardo; Bell, Jean Pierre

2015-01-01

A new deforestation and land-use change scenario generator model (FOREST-SAGE) is presented that is designed to interface directly with dynamic vegetation models used in latest generation earth system models. The model requires a regional-scale scenario for aggregate land-use change that may be time-dependent, provided by observational studies or by regional land-use change/economic models for future projections. These land-use categories of the observations/economic model are first translated into equivalent plant function types used by the particular vegetation model, and then FOREST-SAGE disaggregates the regional-scale scenario to the local grid-scale of the earth system model using a set of risk-rules based on factors such as proximity to transport networks, distance weighted population density, forest fragmentation and presence of protected areas and logging concessions. These rules presently focus on the conversion of forest to agriculture and pasture use, but could be generalized to other land use change conversions. After introducing the model, an evaluation of its performance is shown for the land-cover changes that have occurred in the Central African Basin from 2001–2010 using retrievals from MODerate Resolution Imaging Spectroradiometer Vegetation Continuous Field data. The model is able to broadly reproduce the spatial patterns of forest cover change observed by MODIS, and the use of the local-scale risk factors enables FOREST-SAGE to improve land use change patterns considerably relative to benchmark scenarios used in the latest Coupled Model Intercomparison Project integrations. The uncertainty to the various risk factors is investigated using an ensemble of investigations, and it is shown that the model is sensitive to the population density, forest fragmentation and reforestation factors specified. PMID:26394392

Modelling landscape dynamics with LST in protected areas of Western Ghats, Karnataka.

PubMed

Ramachandra, T V; Bharath, Setturu; Gupta, Nimish

2018-01-15

Forest ecosystems sustain biota on the earth as they are habitat to diverse biotic species, arrests soil erosion, play a crucial role in water cycle, sequester carbon, and helps in mitigating the impacts of global warming. Large scale land use land cover (LULC) change leading to deforestation is one of the drivers of global climate changes and alteration of biogeochemical cycles with significant consequences in ecosystem services and biodiversity. This has necessitated the investigation of LULC by mapping, monitoring and modelling spatio-temporal patterns and evaluating these in the context of human-environment interactions. The current work investigates LULC changes with temperature dynamics of select protected areas in Western Ghats. The land use analyses reveal changes in the forest cover across Kudremukh National Park (KNP), Rajiv Gandhi Tiger Reserve (RTR), Bandipur Tiger Reserve (BTR). KNP region has lost evergreen forest cover during 1973-2016 from 33.46 to 27.22%, while BTR lost deciduous cover from 61.69 to 47.3% due to mining, horticulture plantations, human habitations, etc. The LST increase has impacted regeneration of species with the induced water stress, etc. CA-Markov modelling was used for forecasting the likely land uses in 2026 and validation was done through Kappa indices. Results highlight decline of evergreen cover in KNP (9%) and deciduous cover in RTR (2%) followed by BTR (3%) with further expansion of plantations, which will impact biodiversity, hydrology and ecology. Insights of LULC dynamics help natural resource managers in evolving appropriate strategies to ensure conservation of threatened biota in Western Ghats. Copyright © 2017 Elsevier Ltd. All rights reserved.

Implementing dynamic root optimization in Noah-MP for simulating phreatophytic root water uptake

USDA-ARS?s Scientific Manuscript database

Plants are known to adjust their root systems to adapt to changing subsurface water conditions. However, most current land surface models (LSMs) use a prescribed, static root profile, which cuts off the interactions between soil moisture and root dynamics. In this paper, we implemented an optimality...

LSD (Landing System Development) Impact Simulation

NASA Astrophysics Data System (ADS)

Ullio, R.; Riva, N.; Pellegrino, P.; Deloo, P.

2012-07-01

In the frame of the Exploration Programs, a soft landing on the planet surface is foreseen. To ensure a successful final landing phase, a landing system by using leg tripod design landing legs with adequate crushable damping system was selected, capable of absorbing the residual velocities (vertical, horizontal and angular) at touch- down, insuring stability. TAS-I developed a numerical non linear dynamic methodology for the landing impact simulation of the Lander system by using a commercial explicit finite element analysis code (i.e. Altair RADIOSS). In this paper the most significant FE modeling approaches and results of the analytical simulation of landing impact are reported, especially with respect to the definition of leg dimensioning loads and the design update of selected parts (if necessary).

Disentangling the effects of climate and people on Sahel vegetation dynamics

NASA Astrophysics Data System (ADS)

Seaquist, J. W.; Hickler, T.; Eklundh, L.; Ardö, J.; Heumann, B. W.

2009-03-01

The Sahel belt of Africa has been the focus of intensive scientific research since the 1960s, spurred on by the chronic vulnerability of its population to recurring drought and the threat of long-term land degradation. But satellite sensors have recently shown that much of the region has experienced significant increases in photosynthetic activity since the early 1980s, thus re-energizing long-standing debates about the role that people play in shaping land surface status, and thus climate at regional scales. In this paper, we test the hypothesis that people have had a measurable impact on vegetation dynamics in the Sahel for the period 1982-2002. We compare potential natural vegetation dynamics predicted by a process-based ecosystem model with satellite-derived greenness observations, and map the agreement between the two across a geographic grid at a spatial resolution of 0.5°. As aggregated data-model agreement is very good, any local differences between the two could be due to human impact. We then relate this agreement metric to state-of-the-art data sets on demographics, pasture, and cropping. Our findings suggest that demographic and agricultural pressures in the Sahel are unable to account for differences between simulated and observed vegetation dynamics, even for the most densely populated areas. But we do identify a weak, positive correlation between data-model agreement and pasture intensity at the Sahel-wide level. This indicates that herding or grazing does not appreciably affect vegetation dynamics in the region. Either people have not had a significant impact on vegetation dynamics in the Sahel or the identification of a human "footprint" is precluded by inconsistent or subtle vegetation response to complex socio-environmental interactions, and/or limitations in the data used for this study. We do not exclude the possibility of a greater human influence on vegetation dynamics over the coming decades with changing land use.

Hydrodynamic Qualities of a 1/10-Size Powered Dynamic Model of the XP5Y-1 Flying Boat in Smooth Water: Langley Tank Model 246, TED No. NACA DE 320

NASA Technical Reports Server (NTRS)

Woodward, David R.; Weinstein, Irving; Whitaker, Walter E., Jr.

1947-01-01

The hydrodynamic characteristics of a 1/10-size powered dynamic model of the XP5Y-1 flying boat were determined in Langley tank no. 1. Stable take-offs were possible at all practicable positions of the center of gravity and flap deflections. An increase in gross load from 123.5 to 150.0 pounds (21.5 percent) had only a slight effect on the stable range for take-off. A decrease in forward acceleration from 3.0 to 1.0 feet per second per second had only a very small effect on the stable range for take-off. In general, the landings were free from skipping except at trims below 6 deg where one skip was encountered at an aft position of the center of gravity. The model porpoised during the landing runout at all positions of the center of gravity when landed at trims above 10 deg. Spray in the propellers was light at the design gross load, and was not considered excessive,at a gross load of 136.0 pounds.

Description and validation of the Simple, Efficient, Dynamic, Global, Ecological Simulator (SEDGES v.1.0)

NASA Astrophysics Data System (ADS)

Paiewonsky, Pablo; Elison Timm, Oliver

2018-03-01

In this paper, we present a simple dynamic global vegetation model whose primary intended use is auxiliary to the land-atmosphere coupling scheme of a climate model, particularly one of intermediate complexity. The model simulates and provides important ecological-only variables but also some hydrological and surface energy variables that are typically either simulated by land surface schemes or else used as boundary data input for these schemes. The model formulations and their derivations are presented here, in detail. The model includes some realistic and useful features for its level of complexity, including a photosynthetic dependency on light, full coupling of photosynthesis and transpiration through an interactive canopy resistance, and a soil organic carbon dependence for bare-soil albedo. We evaluate the model's performance by running it as part of a simple land surface scheme that is driven by reanalysis data. The evaluation against observational data includes net primary productivity, leaf area index, surface albedo, and diagnosed variables relevant for the closure of the hydrological cycle. In this setup, we find that the model gives an adequate to good simulation of basic large-scale ecological and hydrological variables. Of the variables analyzed in this paper, gross primary productivity is particularly well simulated. The results also reveal the current limitations of the model. The most significant deficiency is the excessive simulation of evapotranspiration in mid- to high northern latitudes during their winter to spring transition. The model has a relative advantage in situations that require some combination of computational efficiency, model transparency and tractability, and the simulation of the large-scale vegetation and land surface characteristics under non-present-day conditions.

Scientific analysis is essential to assess biofuel policy effects: in response to the paper by Kim and Dale on "Indirect land use change for biofuels: Testing predictions and improving analytical methodologies"

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

Kline, Keith L; Oladosu, Gbadebo A; Dale, Virginia H

2011-01-01

Vigorous debate on the effects of biofuels derives largely from the changes in land use estimated using economic models designed mainly for the analysis of agricultural trade and markets. The models referenced for land-use change (LUC) analysis in the U.S. Environmental Protection Agency Final Rule on the Renewable Fuel Standard include GTAP, FAPRI-CARD, and FASOM. To address bioenergy impacts, these models were expanded and modified to facilitate simulations of hypothesized LUC. However, even when models use similar basic assumptions and data, the range of LUC results can vary by ten-fold or more. While the market dynamics simulated in these modelsmore » include processes that are important in estimating effects of biofuel policies, the models have not been validated for estimating land-use changes and employ crucial assumptions and simplifications that contradict empirical evidence.« less

Effects of anthropogenic land-subsidence on river flood hazard: a case study in Ravenna, Italy

NASA Astrophysics Data System (ADS)

Carisi, Francesca; Domeneghetti, Alessio; Castellarin, Attilio

2015-04-01

Can differential land-subsidence significantly alter the river flooding dynamics, and thus flood risk in flood prone areas? Many studies show how the lowering of the coastal areas is closely related to an increase in the flood-hazard due to more important tidal flooding and see level rise. On the contrary, the literature on the relationship between differential land-subsidence and possible alterations to riverine flood-hazard of inland areas is still sparse, while several areas characterized by significant land-subsidence rates during the second half of the 20th century experienced an intensification in both inundation magnitude and frequency. This study investigates the possible impact of a significant differential ground lowering on flood hazard in proximity of Ravenna, which is one of the oldest Italian cities, former capital of the Western Roman Empire, located a few kilometers from the Adriatic coast and about 60 km south of the Po River delta. The rate of land-subsidence in the area, naturally in the order of a few mm/year, dramatically increased up to 110 mm/year after World War II, primarily due to groundwater pumping and a number of deep onshore and offshore gas production platforms. The subsidence caused in the last century a cumulative drop larger than 1.5 m in the historical center of the city. Starting from these evidences and taking advantage of a recent digital elevation model of 10m resolution, we reconstructed the ground elevation in 1897 for an area of about 65 km2 around the city of Ravenna. We referred to these two digital elevation models (i.e. current topography and topographic reconstruction) and a 2D finite-element numerical model for the simulation of the inundation dynamics associated with several levee failure scenarios along embankment system of the river Montone. For each scenario and digital elevation model, the flood hazard is quantified in terms of water depth, speed and dynamics of the flooding front. The comparison enabled us to quantify alterations to the flooding hazard due to large and rapid differential land-subsidence, shedding some light on whether to consider anthropogenic land-subsidence among the relevant human-induced drivers of flood-risk change.

Ditching Investigation of a 1/10-Scale Model of the Grumman F9F-2 Airplane, TED No. NACA DE 335

NASA Technical Reports Server (NTRS)

Fisher, Lloyd J.; McBride, Ellis E.

1955-01-01

An investigation was made of a 1/10-scale dynamically similar model of the Grumman FgF-2 airplane to study its behavior when ditched. The model was landed in calm water at the Langley Tank No. 2 monorail. Various landing attitudes, speeds, and configurations were investigated. The behavior of the model was determined from visual observations, acceleration records, and motion-picture records of the ditchings. Data are presented in tabular form, sequence photographs, time-history acceleration curves, and plots of attitude and speed against distance after contact.

Chapman Conference on the Hydrologic Aspects of Global Climate Change, Lake Chelan, WA, June 12-14, 1990, Selected Papers

NASA Technical Reports Server (NTRS)

Lettenmaier, Dennis P. (Editor); Rind, D. (Editor)

1992-01-01

The present conference on the hydrological aspects of global climate change discusses land-surface schemes for future climate models, modeling of the land-surface boundary in climate models as a composite of independent vegetation, a land-surface hydrology parameterizaton with subgrid variability for general circulation models, and conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models. Attention is given to the impact of global warming on river runoff, the influence of atmospheric moisture transport on the fresh water balance of the Atlantic drainage basin, a comparison of observations and model simulations of tropospheric water vapor, and the use of weather types to disaggregate the prediction of general circulation models. Topics addressed include the potential response of an Arctic watershed during a period of global warming and the sensitivity of groundwater recharge estimates to climate variability and change.

Assessing the impact of urban land cover composition on CO2 flux

NASA Astrophysics Data System (ADS)

Becker, K.; Hinkle, C.

2013-12-01

Urbanization is an ever increasing trend in global land use change, and has been identified as a key driver of CO2 emissions. Therefore, understanding how urbanization affects CO2 flux across a range of climatic zones and development patterns is critical to projecting the impact of future land use on CO2 flux dynamics. A growing number of studies are applying the eddy covariance method to urban areas to quantify the CO2 flux dynamics of these systems. However, interpretation of eddy covariance data in these urban systems presents a challenge, particularly in areas with high heterogeneity due to a mixing of built and green space. Here we present a study aimed at establishing a relationship between land cover composition and CO2 flux for a heterogeneous urban area of Orlando, FL. CO2 flux has been measured at this site for > 4 years using an open path eddy covariance system. Land cover at this site was classified into built and green space, and relative weight of both land covers were calculated for each 30 min CO2 flux measurement using the Schuepp model and a source area based on +/- one standard deviation of wind direction. The results of this analysis established a relationship between built land cover and CO2 flux within the measured footprint of this urban area. These results, in combination with future projected land use data, will be a valuable resource for providing insight into the impact of future urbanization on CO2 flux dynamics in this region.

CCN numerical simulations for the GoAmazon with the OLAM model

NASA Astrophysics Data System (ADS)

Ramos-da-Silva, R.; Haas, R.; Barbosa, H. M.; Machado, L.

2015-12-01

Manaus is a large city in the center of the Amazon rainforest. The GoAmazon field project is exploring the region through various data collection and modeling to investigate in impacts of the urban polluted plume on the surrounding pristine areas. In this study a numerical model was applied to simulate the atmospheric dynamics and the Cloud Condensation Nucleai (CCN) concentrations evolution. Simulations with and without the urban plume was performed to identify its dynamics and local impacts. The results show that the land surface characteristics has important hole on the CCN distribution and rainfall over the region. At the south of Manaus the atmospheric dynamics is dominated by the cloud streets that are aligned with the trade winds and the Amazon River. At the north of Manaus, the Negro River produces the advection of a more stable atmosphere causing a higher CCN concentration on the boundary layer. Assuming a local high CCN concentration at the Manaus boundary layer region, the simulations show that the land-atmosphere interaction sets important dynamics on the plume. The model shows that the CCN plume moves along with the flow towards southwest of Manaus following the cloud streets and the river direction having the highest concentrations over the most stable water surface regions.

Dynamic root distributions in ecohydrological modeling: A case study at Walnut Gulch Experimental Watershed

NASA Astrophysics Data System (ADS)

Sivandran, Gajan; Bras, Rafael L.

2013-06-01

Arid regions are characterized by high variability in the arrival of rainfall, and species found in these areas have adapted mechanisms to ensure the capture of this scarce resource. In particular, the rooting strategies employed by vegetation can be critical to their survival. However, land surface models currently prescribe rooting profiles as a function of only the plant functional type of interest with no consideration for the soil texture or rainfall regime of the region being modeled. Additionally, these models do not incorporate the ability of vegetation to dynamically alter their rooting strategies in response to transient changes in environmental forcings or competition from other plant species and therefore tend to underestimate the resilience of these ecosystems. To address the simplicity of the current representation of roots in land surface models, a new dynamic rooting scheme was incorporated into the framework of the distributed ecohydrological model tRIBS+VEGGIE. The new scheme optimizes the allocation of carbon to the root zone to reduce the perceived stress of the vegetation, so that root profiles evolve based upon local climate and soil conditions. The ability of the new scheme to capture the complex dynamics of natural systems was evaluated by comparisons to hourly timescale energy flux, soil moisture, and vegetation growth observations from the Walnut Gulch Experimental Watershed, Arizona. Robust agreement was found between the model and observations, providing confidence that the improved model is able to capture the multidirectional interactions between climate, soil, and vegetation at this site.

Updating representation of land surface-atmosphere feedbacks in airborne campaign modeling analysis

NASA Astrophysics Data System (ADS)

Huang, M.; Carmichael, G. R.; Crawford, J. H.; Chan, S.; Xu, X.; Fisher, J. A.

2017-12-01

An updated modeling system to support airborne field campaigns is being built at NASA Ames Pleiades, with focus on adjusting the representation of land surface-atmosphere feedbacks. The main updates, referring to previous experiences with ARCTAS-CARB and CalNex in the western US to study air pollution inflows, include: 1) migrating the WRF (Weather Research and Forecasting) coupled land surface model from Noah to improved/more complex models especially Noah-MP and Rapid Update Cycle; 2) enabling the WRF land initialization with suitably spun-up land model output; 3) incorporating satellite land cover, vegetation dynamics, and soil moisture data (i.e., assimilating Soil Moisture Active Passive data using the ensemble Kalman filter approach) into WRF. Examples are given of comparing the model fields with available aircraft observations during spring-summer 2016 field campaigns taken place at the eastern side of continents (KORUS-AQ in South Korea and ACT-America in the eastern US), the air pollution export regions. Under fair weather and stormy conditions, air pollution vertical distributions and column amounts, as well as the impact from land surface, are compared. These help identify challenges and opportunities for LEO/GEO satellite remote sensing and modeling of air quality in the northern hemisphere. Finally, we briefly show applications of this system on simulating Australian conditions, which would explore the needs for further development of the observing system in the southern hemisphere and inform the Clean Air and Urban Landscapes (https://www.nespurban.edu.au) modelers.

Meta-analysis of high-latitude nitrogen-addition and warming studies imply ecological mechanisms overlooked by land models

NASA Astrophysics Data System (ADS)

Bouskill, N. J.; Riley, W. J.; Tang, J.

2014-08-01

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the atmosphere. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the above and belowground high-latitude ecosystem responses to warming and nitrogen addition, and identified mechanisms absent, or poorly parameterized in CLM4.5. While the two model versions predicted similar trajectories for soil carbon stocks following both types of perturbation, other variables (e.g., belowground respiration) differed from the observations in both magnitude and direction, indicating the underlying mechanisms are inadequate for representing high-latitude ecosystems. The observational synthesis attribute these differences to missing representations of microbial dynamics, characterization of above and belowground functional processes, and nutrient competition. We use the observational meta-analyses to discuss potential approaches to improving the current models (e.g., the inclusion of dynamic vegetation or different microbial functional guilds), however, we also raise a cautionary note on the selection of data sets and experiments to be included in a meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average =72 kg ha-1 yr-1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which preclude a rigorous evaluation of the model responses to nitrogen perturbation. Overall, we demonstrate here that elucidating ecological mechanisms via meta-analysis can identify deficiencies in both ecosystem models and empirical experiments.

Meta-analysis of high-latitude nitrogen-addition and warming studies imply ecological mechanisms overlooked by land models

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

Bouskill, N. J.; Riley, W. J.; Tang, J.

2014-08-18

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the atmosphere. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the above and belowground high-latitude ecosystem responses to warming and nitrogen addition, and identified mechanisms absent, or poorly parameterized in CLM4.5. While the two model versions predicted similar trajectories for soil carbon stocks following both types of perturbation, other variables (e.g., belowground respiration) differedmore » from the observations in both magnitude and direction, indicating the underlying mechanisms are inadequate for representing high-latitude ecosystems. The observational synthesis attribute these differences to missing representations of microbial dynamics, characterization of above and belowground functional processes, and nutrient competition. We use the observational meta-analyses to discuss potential approaches to improving the current models (e.g., the inclusion of dynamic vegetation or different microbial functional guilds), however, we also raise a cautionary note on the selection of data sets and experiments to be included in a meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average =72 kg ha -1 yr -1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which preclude a rigorous evaluation of the model responses to nitrogen perturbation. Overall, we demonstrate here that elucidating ecological mechanisms via meta-analysis can identify deficiencies in both ecosystem models and empirical experiments.« less

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.

Assessing the impacts of land use on downstream water quality using a hydrologically sensitive area concept.

PubMed

Giri, Subhasis; Qiu, Zeyuan; Zhang, Zhen

2018-05-01

Understanding the relationship between land use and water quality is essential to improve water quality through carefully managing landscape change. This study applies a linear mixed model at both watershed and hydrologically sensitive areas (HSAs) scales to assess such a relationship in 28 northcentral New Jersey watersheds located in a rapidly urbanizing region in the United States. Two models differ in terms of the geographic scope used to derive land use matrices that quantify land use conditions. The land use matrices at the watershed and HSAs scales represent the land use conditions in these watersheds and their HSAs, respectively. HSAs are the hydrological "hotspots" in a watershed that are prone to runoff generation during storm events. HSAs are derived using a soil topographic index (STI) that predicts hydrological sensitivity of a landscape based on a variable source area hydrology concept. The water quality indicators in these models are total nitrogen (TN), total phosphorus (TP) and total suspended solids (TSS) concentrations in streams observed at the watershed outlets. The modeling results suggest that presence of low density urban land, agricultural land and wetlands elevate while forest decreases TN, TP and/or TSS concentrations in streams. The watershed scale model tends to emphasize the role of agricultural lands in water quality degradation while the HSA scale model highlights the role of forest in water quality improvement. This study supports the hypothesis that even though HSAs are relatively smaller area compared to watershed, still the land uses within HSAs have similar impacts on downstream water quality as the land uses in entire watersheds, since both models have negligible differences in model evaluation parameters. Inclusion of HSAs brings an interesting perspective to understand the dynamic relationships between land use and water quality. Copyright © 2018 Elsevier Ltd. All rights reserved.

Propulsive Reaction Control System Model

NASA Technical Reports Server (NTRS)

Brugarolas, Paul; Phan, Linh H.; Serricchio, Frederick; San Martin, Alejandro M.

2011-01-01

This software models a propulsive reaction control system (RCS) for guidance, navigation, and control simulation purposes. The model includes the drive electronics, the electromechanical valve dynamics, the combustion dynamics, and thrust. This innovation follows the Mars Science Laboratory entry reaction control system design, and has been created to meet the Mars Science Laboratory (MSL) entry, descent, and landing simulation needs. It has been built to be plug-and-play on multiple MSL testbeds [analysis, Monte Carlo, flight software development, hardware-in-the-loop, and ATLO (assembly, test and launch operations) testbeds]. This RCS model is a C language program. It contains two main functions: the RCS electronics model function that models the RCS FPGA (field-programmable-gate-array) processing and commanding of the RCS valve, and the RCS dynamic model function that models the valve and combustion dynamics. In addition, this software provides support functions to initialize the model states, set parameters, access model telemetry, and access calculated thruster forces.

Response of South American Ecosystems to Precipitation Variability

NASA Astrophysics Data System (ADS)

Knox, R. G.; Kim, Y.; Longo, M.; Medvigy, D.; Wang, J.; Moorcroft, P. R.; Bras, R. L.

2009-12-01

The Ecosystem Demography Model 2 is a dynamic ecosystem model and land surface energy balance model. ED2 discretizes landscapes of particular terrain and meteorology into fractional areas of unique disturbance history. Each fraction, defined by a shared vertical soil column and canopy air space, contains a stratum of plant groups unique in functional type, size and number density. The result is a vertically distributed representation of energy transfer and plant dynamics (mortality, productivity, recruitment, disturbance, resource competition, etc) that successfully approximates the behaviour of individual-based vegetation models. In previous exercises simulating Amazonian land surface dynamics with ED 2, it was observed that when using grid averaged precipitation as an external forcing the resulting water balance typically over-estimated leaf interception and leaf evaporation while under estimating through-fall and transpiration. To investigate this result, two scenario were conducted in which land surface biophysics and ecosystem demography over the Northern portion of South America are simulated over ~200 years: (1) ED2 is forced with grid averaged values taken from the ERA40 reanalysis meteorological dataset; (2) ED2 is forced with ERA40 reanalysis, but with its precipitation re-sampled to reflect statistical qualities of point precipitation found at rain gauge stations in the region. The findings in this study suggest that the equilibrium moisture states and vegetation demography are co-dependent and show sensitivity to temporal variability in precipitation. These sensitivities will need to be accounted for in future projections of coupled climate-ecosystem changes in South America.

Identification of Dust Source Regions at High-Resolution and Dynamics of Dust Source Mask over Southwest United States Using Remote Sensing Data

NASA Astrophysics Data System (ADS)

Sprigg, W. A.; Sahoo, S.; Prasad, A. K.; Venkatesh, A. S.; Vukovic, A.; Nickovic, S.

2015-12-01

Identification and evaluation of sources of aeolian mineral dust is a critical task in the simulation of dust. Recently, time series of space based multi-sensor satellite images have been used to identify and monitor changes in the land surface characteristics. Modeling of windblown dust requires precise delineation of mineral dust source and its strength that varies over a region as well as seasonal and inter-annual variability due to changes in land use and land cover. Southwest USA is one of the major dust emission prone zone in North American continent where dust is generated from low lying dried-up areas with bare ground surface and they may be scattered or appear as point sources on high resolution satellite images. In the current research, various satellite derived variables have been integrated to produce a high-resolution dust source mask, at grid size of 250 m, using data such as digital elevation model, surface reflectance, vegetation cover, land cover class, and surface wetness. Previous dust source models have been adopted to produce a multi-parameter dust source mask using data from satellites such as Terra (Moderate Resolution Imaging Spectroradiometer - MODIS), and Landsat. The dust source mask model captures the topographically low regions with bare soil surface, dried-up river plains, and lakes which form important source of dust in southwest USA. The study region is also one of the hottest regions of USA where surface dryness, land use (agricultural use), and vegetation cover changes significantly leading to major changes in the areal coverage of potential dust source regions. A dynamic high resolution dust source mask have been produced to address intra-annual change in the aerial extent of bare dry surfaces. Time series of satellite derived data have been used to create dynamic dust source masks. A new dust source mask at 16 day interval allows enhanced detection of potential dust source regions that can be employed in the dust emission and transport pathways models for better estimation of emission of dust during dust storms, particulate air pollution, public health risk assessment tools and decision support systems.

Dynamic modelling of future land use change under urbanization and climate change pressures: application to a case study in central Belgium

NASA Astrophysics Data System (ADS)

Jacquemin, I.; Fontaine, C. M.; Dendoncker, N.; François, L.; De Vreese, R.; Marek, A.; Mortelmans, D.; Van Herzele, A.; Devillet, G.

2012-04-01

Projecting the future of the evolution of socio-ecological systems to analyse their sustainability under climate or other environmental changes is not straightforward. Current projections usually use process-oriented models describing the complex interactions within the physical/biological systems (ecosystems), while the socio-economic constraints are represented with the help of scenarios. However, the actual evolution can be expected to be much more complex, because of the mutual interactions between ecological and socio-economic systems. To represent these interactions, models must integrate the complex process of human decision at individual or society levels. Moreover, models must be spatially explicit, defining elementary spatial units on which can act both the physical factors and the human decision process. These spatial units (e.g., farm fields) must be described not only in terms of energy, water, carbon and nutrient flows, but also in terms of the flow of ecosystem goods and services (EGS) they provide to the society together with the management costs required to sustain them. The provision of EGS may be altered in the future in response to changes in the climate system and the environment, but also through various human pressures on the landscape such as urbanization, as well as through the reaction of human societies to these changes in EGS provision. In the VOTES ("Valuation Of Terrestrial Ecosystem Services in a multifunctional peri-urban space") project, we attempt to model this coupled socio-ecological system by combining a dynamic vegetation model (DVM) with an agent-based model (ABM). The DVM (CARAIB; Dury et al., iForest - Biogeosciences and Forestry, 4:82-99, 2011) model describes the evolution of physical and biological processes in the ecosystems, i.e. the impact of climate change and land management on the energy, water and carbon budgets, as well as the productivity of each simulated plant species present on each land unit. The original version of the model developed for natural vegetation has been upgraded to include crop systems and pastures. The ABM (Murray-Rust, Journal of Land Use Science, 6(2-3):83-99, 2011) describes the management choices (e.g., crop rotation, intensive agriculture or organic farming, etc) for each land plot, as well as the possible change in their affectation (e.g., conversion of farm fields to residential areas in response to urbanization), under different socio-economic contexts described in the storyline of three scenarios depicting general societal orientations (business-as-usual; market oriented; sustainability oriented). As a result, the ABM produces a dynamic evolution of land use and management options to be passed on to the DVM for further analysis. The outputs from the DVM allow evaluating quantitatively the provision of EGS by each land plot. This DVM-ABM modelling tool is thus able to describe the future evolution of land use and land cover, as well as of EGS production, in the context of socio-economic scenarios. The model is applied to a case study area covering four municipalities located in central Belgium close to Brussels and Leuven. The area is mostly composed of agricultural fields (crops and meadows), residential areas and a large protected forest (Meerdaalbos) and is subject to intense urbanization pressure due to the proximity to Brussels.

Satellite image simulations for model-supervised, dynamic retrieval of crop type and land use intensity

NASA Astrophysics Data System (ADS)

Bach, H.; Klug, P.; Ruf, T.; Migdall, S.; Schlenz, F.; Hank, T.; Mauser, W.

2015-04-01

To support food security, information products about the actual cropping area per crop type, the current status of agricultural production and estimated yields, as well as the sustainability of the agricultural management are necessary. Based on this information, well-targeted land management decisions can be made. Remote sensing is in a unique position to contribute to this task as it is globally available and provides a plethora of information about current crop status. M4Land is a comprehensive system in which a crop growth model (PROMET) and a reflectance model (SLC) are coupled in order to provide these information products by analyzing multi-temporal satellite images. SLC uses modelled surface state parameters from PROMET, such as leaf area index or phenology of different crops to simulate spatially distributed surface reflectance spectra. This is the basis for generating artificial satellite images considering sensor specific configurations (spectral bands, solar and observation geometries). Ensembles of model runs are used to represent different crop types, fertilization status, soil colour and soil moisture. By multi-temporal comparisons of simulated and real satellite images, the land cover/crop type can be classified in a dynamically, model-supervised way and without in-situ training data. The method is demonstrated in an agricultural test-site in Bavaria. Its transferability is studied by analysing PROMET model results for the rest of Germany. Especially the simulated phenological development can be verified on this scale in order to understand whether PROMET is able to adequately simulate spatial, as well as temporal (intra- and inter-season) crop growth conditions, a prerequisite for the model-supervised approach. This sophisticated new technology allows monitoring of management decisions on the field-level using high resolution optical data (presently RapidEye and Landsat). The M4Land analysis system is designed to integrate multi-mission data and is well suited for the use of Sentinel-2's continuous and manifold data stream.

The dynamical interactions of Amazon deforestation, intensification of cattle ranching and technology adoption: insights from a socio-ecological model

NASA Astrophysics Data System (ADS)

Müller-Hansen, Finn; Heitzig, Jobst; Donges, Jonathan F.; Cardoso, Manoel F.; Kurths, Jürgen; Thonicke, Kirsten

2017-04-01

Deforestation in the tropics - with vast consequences for the ecosystem and climate - is mainly driven by subsequent land use, which is not only determined by environmental and economic constraints but also influenced by the use of different production technologies. Inefficient production technologies can lead to excessive use of land, especially in areas where land is easily available and accessible. Here, the adoption of new technologies could help to use already converted land more intensively and ease pressures on ecologically valuable areas. In this study, we take the Brazilian Amazon as a prominent example region to explore the interplay of land-use decisions with environmental and economic dynamics in the process of land-use intensification and frontier expansion. Expansion of pasture land for cattle ranching to satisfy increasing domestic and international demands is one of the important drivers for deforestation in the Brazilian Amazon. Pasture run-down and following land abandonment further drive the expansion of deforestation frontiers into pristine forests. Therefore, intensification of livestock production, especially better pasture management, could potentially reduce deforestation. However, a number of reasons including the large spatial extent of the region make the process of comparing the effectiveness of different management techniques, technologies and policies in the region difficult. Therefore, the effectiveness and possible outcomes of policies to foster intensification are highly debated in the literature. Some authors deny that intensification policies are a viable option to spare forests as long as they are not a scarce resource [1] while others insist that intensification has an effect if only supported by the right policies [2]. In this presentation, we introduce a concise agent-based model to study conditions under which intensification can reduce deforestation and explore the trade-offs between intensified and extensive land uses. While most agent-based models in land science are developed for small study regions, our approach is scalable also to regional levels and for this purpose abstracts from many local specificities. In the proposed model, a collection of cattle ranchers interacts with the local environment via decisions to convert forest into pasture land and manage this pasture. Deforestation and land abandonment is traced by simple land-cover succession equations and ecological dynamics consider the evolution of pasture productivity depending on pasture management, deforestation and tree regrowth. Agent decisions are captured by heuristic strategies depending on economic and ecological constraints. Agents can follow either an extensive strategy, corresponding to traditional cattle ranching with fallow periods and slash-and-burn fertilization, or an intensive strategy, i.e. cattle ranching with high inputs such as machinery and industrial fertilizers. The choice of the production strategy is modeled as a social learning process: Agents are located on a geometric network representing neighborhood and acquaintance relations and imitate the successful strategies of their neighbors. We will present a comprehensive analysis of the model and discuss conditions that foster sustainable land use. Finally, we will give an outlook at possible extensions of the model and applications to issues such as compliance with Brazil's Forest Code and feedbacks from changes in climate. References: [1] Kaimowitz, David and Arild Angelsen (2008). "Will Livestock Intensification Help Save Latin America's Tropical Forests?" In: Journal of Sustainable Forestry 27.1-2, pp. 6-24. [2] Cohn, Avery S, Aline Mosnier, Petr Havlík, Hugo Valin, Mario Herrero, Erwin Schmid, Michael O'Hare, and Michael Obersteiner (2014). "Cattle ranching intensification in Brazil can reduce global greenhouse gas emissions by sparing land from deforestation." In: Proceedings of the National Academy of Sciences of the United States of America 111.20, pp. 7236-7241.

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

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less

Simulating the conversion of rural settlements to town land based on multi-agent systems and cellular automata.

PubMed

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans.

Towards a community Earth System Model

NASA Astrophysics Data System (ADS)

Blackmon, M.

2003-04-01

The Community Climate System Model, version 2 (CCSM2), was released in June 2002. CCSM2 has several new components and features, which I will discuss briefly. I will also show a few results from a multi-century equilibrium run with this model, emphasizing the improvements over the earlier simulation using the original CSM. A few flaws and inadequacies in CCSM2 have been identified. I will also discuss briefly work underway to improve the model and present results, if available. CCSM2, with improvements, will be the basis for the development of a Community Earth System Model (CESM). The highest priority for expansion of the model involves incorporation of biogeosciences into the coupled model system, with emphasis given to the carbon, nitrogen and iron cycles. The overall goal of the biogeosciences project within CESM is to understand the regulation of planetary energetics, planetary ecology, and planetary metabolism through exchanges of energy, momentum, and materials among atmosphere, land, and ocean, and the response of the climate system through these processes to changes in land cover and land use. In particular, this research addresses how biogeochemical coupling of carbon, nitrogen, and iron cycles affects climate and how human perturbations of these cycles alter climate. To accomplish these goals, the Community Land Model, the land component of CCSM2, is being developed to include river routing, carbon and nitrogen cycles, emissions of mineral aerosols and biogenic volatile organic compounds, dry deposition of various gases, and vegetation dynamics. The carbon and nitrogen cycles are being implemented using parameterizations developed as part of a state-of-the-art ecosystem biogeochemistry model. The primary goal of this research is to provide an accurate net flux of CO2 between the land and the atmosphere so that CESM can be used to study the dynamics of the coupled climate-carbon system. Emissions of biogenic volatile organic compounds are also based on a state-of-the-art emissions model and depend on plant type, leaf area index, photosynthetically active radiation, and leaf temperature. Dust emissions and deposition are being developed to implement a fully coupled dust cycle in CCSM, including the radiative effects of dust and carbon feedbacks related to fertilization of ocean and terrestrial ecosystems. Dust mobilization depends on surface wind speed, soil moisture, plant cover, and soil texture. Dust dry deposition processes include sedimentation and turbulent mix-out. A major research focus is how natural and human-mediated changes in land cover and ecosystem functions alter surface energy fluxes, the hydrological cycle, and biogeochemical cycles. Human land uses include conversion of natural vegetation to cropland, soil degradation, and urbanization. Climate feedbacks associated with natural changes in land cover are being assessed by developing and implementing a model of natural vegetation dynamics for use with the Community Land Model. Development of a marine ecosystem model is also underway. The ecosystem model is based on the global, mixed-layer marine ecosystem model of Moore et al., which includes parameterizations for such things as iron limitation and scavenging, zooplankton grazing, nitrogen fixation, calcification, and ballast-based remineralization. A series of experiments is being planned to assess the coupling of the ecology to the biogeochemistry, to adequately tune some of the model parameters that are poorly constrained by data, to explore new parameterizations and processes (e.g., riverine and atmospheric inputs of nutrients), and to conduct uncoupled application studies (e.g., deliberate carbon sequestration, retrospective historical simulations, iron-dust deposition response). Longer term plans include investigating biogeochemical processes in the coastal zone and how to incorporate these processes into a global ocean model, either through subgrid-scale parameterizations or model nesting. A Whole Atmosphere Community Climate Model(WACCM) is being developed. The vertical extent of the model is 150 km at present, but extension to 500 km is eventually expected. Interactive chemistry is being incorporated. This model will be used as the atmospheric component of CESM for some experiments. One expected application is the study of solar variability and its impact on climate variability in the troposphere and at the atmosphere, ocean, land interface. Preliminary results using some of these model components will be shown. A timeline for development and use of the models will be given.

Interactions between nitrogen deposition, land cover conversion, and climate change determine the contemporary carbon balance of Europe

NASA Astrophysics Data System (ADS)

Churkina, G.; Zaehle, S.; Hughes, J.; Viovy, N.; Chen, Y.; Jung, M.; Heumann, B. W.; Ramankutty, N.; Rödenbeck, C.; Heimann, M.; Jones, C.

2010-03-01

European ecosystems are thought to uptake significant amounts of carbon, but neither the rate nor the contributions of the underlying processes are well known. In the second half of the 20th century, carbon dioxide concentrations have risen by more than 100 ppm, atmospheric nitrogen deposition has more than doubled, and European mean temperatures were increasing by 0.02 °C per year. The extents of forest and grasslands have increase with the respective rates of 5800 km2 yr-1 and 1100 km2 yr-1 as agricultural land has been abandoned at a rate of 7000 km2 yr-1. In this study, we analyze the responses of European land ecosystems to the aforementioned environmental changes using results from four process-based ecosystem models: BIOME-BGC, JULES, ORCHIDEE, and O-CN. All four models suggest that European terrestrial ecosystems sequester carbon at a rate of 100 TgC yr-1 (1980-2007 mean) with strong interannual variability (± 85 TgC yr-1) and a substantial inter-model uncertainty (± 45 TgC yr-1). Decadal budgets suggest that there has been a slight increase in terrestrial net carbon storage from 85 TgC yr-1 in 1980-1989 to 114 TgC yr-1 in 2000-2007. The physiological effect of rising CO2 in combination with nitrogen deposition and forest re-growth have been identified as the important explanatory factors for this net carbon storage. Changes in the growth of woody vegetation are an important contributor to the European carbon sink. Simulated ecosystem responses were more consistent for the two models accounting for terrestrial carbon-nitrogen dynamics than for the two models which only accounted for carbon cycling and the effects of land cover change. Studies of the interactions of carbon-nitrogen dynamics with land use changes are needed to further improve the quantitative understanding of the driving forces of the European land carbon balance.

An increase in aerosol burden due to the land-sea warming contrast

NASA Astrophysics Data System (ADS)

Hassan, T.; Allen, R.; Randles, C. A.

2017-12-01

Climate models simulate an increase in most aerosol species in response to warming, particularly over the tropics and Northern Hemisphere midlatitudes. This increase in aerosol burden is related to a decrease in wet removal, primarily due to reduced large-scale precipitation. Here, we show that the increase in aerosol burden, and the decrease in large-scale precipitation, is related to a robust climate change phenomenon—the land/sea warming contrast. Idealized simulations with two state of the art climate models, the National Center for Atmospheric Research Community Atmosphere Model version 5 (NCAR CAM5) and the Geophysical Fluid Dynamics Laboratory Atmospheric Model 3 (GFDL AM3), show that muting the land-sea warming contrast negates the increase in aerosol burden under warming. This is related to smaller decreases in near-surface relative humidity over land, and in turn, smaller decreases in large-scale precipitation over land—especially in the NH midlatitudes. Furthermore, additional idealized simulations with an enhanced land/sea warming contrast lead to the opposite result—larger decreases in relative humidity over land, larger decreases in large-scale precipitation, and larger increases in aerosol burden. Our results, which relate the increase in aerosol burden to the robust climate projection of enhanced land warming, adds confidence that a warmer world will be associated with a larger aerosol burden.

Noah-MP-Crop: Introducing dynamic crop growth in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Liu, Xing; Chen, Fei; Barlage, Michael; Zhou, Guangsheng; Niyogi, Dev

2016-12-01

Croplands are important in land-atmosphere interactions and in the modification of local and regional weather and climate; however, they are poorly represented in the current version of the coupled Weather Research and Forecasting/Noah with multiparameterization (Noah-MP) land surface modeling system. This study introduced dynamic corn (Zea mays) and soybean (Glycine max) growth simulations and field management (e.g., planting date) into Noah-MP and evaluated the enhanced model (Noah-MP-Crop) at field scales using crop biomass data sets, surface heat fluxes, and soil moisture observations. Compared to the generic dynamic vegetation and prescribed-leaf area index (LAI)-driven methods in Noah-MP, the Noah-MP-Crop showed improved performance in simulating leaf area index (LAI) and crop biomass. This model is able to capture the seasonal and annual variability of LAI and to differentiate corn and soybean in peak values of LAI as well as the length of growing seasons. Improved simulations of crop phenology in Noah-MP-Crop led to better surface heat flux simulations, especially in the early period of growing season where current Noah-MP significantly overestimated LAI. The addition of crop yields as model outputs expand the application of Noah-MP-Crop to regional agriculture studies. There are limitations in the use of current growing degree days (GDD) criteria to predict growth stages, and it is necessary to develop a new method that combines GDD with other environmental factors, to more accurately define crop growth stages. The capability introduced in Noah-MP allows further crop-related studies and development.

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.

A Dynamical Downscaling study over the Great Lakes Region Using WRF-Lake: Historical Simulation

NASA Astrophysics Data System (ADS)

Xiao, C.; Lofgren, B. M.

2014-12-01

As the largest group of fresh water bodies on Earth, the Laurentian Great Lakes have significant influence on local and regional weather and climate through their unique physical features compared with the surrounding land. Due to the limited spatial resolution and computational efficiency of general circulation models (GCMs), the Great Lakes are geometrically ignored or idealized into several grid cells in GCMs. Thus, the nested regional climate modeling (RCM) technique, known as dynamical downscaling, serves as a feasible solution to fill the gap. The latest Weather Research and Forecasting model (WRF) is employed to dynamically downscale the historical simulation produced by the Geophysical Fluid Dynamics Laboratory-Coupled Model (GFDL-CM3) from 1970-2005. An updated lake scheme originated from the Community Land Model is implemented in the latest WRF version 3.6. It is a one-dimensional mass and energy balance scheme with 20-25 model layers, including up to 5 snow layers on the lake ice, 10 water layers, and 10 soil layers on the lake bottom. The lake scheme is used with actual lake points and lake depth. The preliminary results show that WRF-Lake model, with a fine horizontal resolution and realistic lake representation, provides significantly improved hydroclimates, in terms of lake surface temperature, annual cycle of precipitation, ice content, and lake-effect snowfall. Those improvements suggest that better resolution of the lakes and the mesoscale process of lake-atmosphere interaction are crucial to understanding the climate and climate change in the Great Lakes region.

DayCent model simulations for estimating soil carbon dynamics and greenhouse gas fluxes from agricultural production systems

USDA-ARS?s Scientific Manuscript database

DayCent is a biogeochemical model of intermediate complexity used to simulate carbon, nutrient, and greenhouse gas fluxes for crop, grassland, forest, and savanna ecosystems. Model inputs include: soil texture and hydraulic properties, current and historical land use, vegetation cover, daily maximum...

Data Synthesis and Data Assimilation at Global Change Experiments and Fluxnet Toward Improving Land Process Models

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

Luo, Yiqi

The project was conducted during the period from 7/1/2012 to 6/30/2017 with three major tasks: (1) data synthesis and development of data assimilation (DA) techniques to constrain modeled ecosystem feedback to climate change; (2) applications of DA techniques to improve process models at different scales from ecosystem to regions and the globe; and 3) improvements of modeling soil carbon (C) dynamics by land surface models. During this period, we have synthesized published data from soil incubation experiments (e.g., Chen et al., 2016; Xu et al., 2016; Feng et al., 2016), global change experiments (e.g., Li et al., 2013; Shi etmore » al., 2015, 2016; Liang et al., 2016) and fluxnet (e.g., Niu et al., 2012., Xia et al., 2015; Li et al., 2016). These data have been organized into multiple data products and have been used to identify general mechanisms and estimate parameters for model improvement. We used the data sets that we collected and the DA techniques to improve model performance of both ecosystem models and global land models. The objectives are: 1) to improve model simulations of litter and soil carbon storage (e.g., Schädel et al., 2013; Hararuk and Luo, 2014; Hararuk et al., 2014; Liang et al., 2015); 2) to explore the effects of CO 2, warming and precipitation on ecosystem processes (e.g., van Groenigen et al., 2014; Shi et al., 2015, 2016; Feng et al., 2017); and 3) to estimate parameters variability in different ecosystems (e.g., Li et al., 2016). We developed a traceability framework, which was based on matrix approaches and decomposed the modeled steady-state terrestrial ecosystem carbon storage capacity into four can trace the difference in ecosystem carbon storage capacity among different biomes to four traceable components: net primary productivity (NPP), baseline C residence times, environmental scalars and climate forcing (Xia et al., 2013). With this framework, we can diagnose the differences in modeled carbon storage across ecosystems, biomes, and models. This framework has been successfully implemented by several global land models, such as CABLE (Xia et al., 2013), LPJ-GUESS (Ahlström et al., 2015), CLM (Hararuk et al., 2014; Huang et al., 2017, submitted; Shi et al., 2017, submitted), and ORCHIDEE (Huang et al., 2017, unpublished). Moreover, we have identified the theoretical foundation of the determinants of transient C storage dynamics by adding another term, C storage potential, to the steady-state traceability framework (Luo et al., 2017). The theoretical foundation of transient C storage dynamics has been applied to develop a transient traceability framework to explore the traceable components of transient C storage dynamics responded to the rising CO 2 and climate change in the two contrasting ecosystem types Duke needleleaved forest and Harvard deciduous broadleaved forest (Jiang et al., 2017, in revision). Overall, with the data synthesis, data assimilation techniques, and the steady-state and transient traceability frameworks, we have greatly improved land process models for predicting responses and feedback of terrestrial C dynamics to global change. The matrix approaches has the potential to be applied in theoretical research on nitrogen and phosphorus cycle, and therefore, the coupling of carbon-nitrogen-phosphorus.« less

Water landing characteristics of a model of a winged reentry vehicle

NASA Technical Reports Server (NTRS)

Stubbs, S. M.

1972-01-01

Proposed manned space shuttle vehicles are expected to land on airport runways. In an emergency situation, however, the vehicle may be required to land on water. A 1/10-scale dynamic model of a winged reentry vehicle was investigated to determine the water landing characteristics. Two configurations of the proposed vehicle were studied. Configuration 1 had a 30 deg negative dihedral of the stabilizer-elevon surface whereas configuration 2 had a 30 deg positive dihedral. Results indicate that the maximum normal accelerations for configurations 1 and 2 when landing in calm water were approximately 8g and 6g, respectively, and the maximum longitudinal accelerations were approximately 5g and 3g, respectively. A small hydroflap was needed to obtain satisfactory calm-water landings with configuration 2, whereas configuration 1 gave good landings without a hydroflap. All landings made in rough water resulted in unsatisfactory motions. For landings made in three different wave sizes, both configurations dived. The maximum normal accelerations for configurations 1 and 2 when landing in waves were -10.1g and -18.7g, respectively, and the maximum longitudinal accelerations for both configurations were approximately 13g.

Growing Land-Sea Temperature Contrast and the Intensification of Arctic Cyclones

NASA Astrophysics Data System (ADS)

Day, Jonathan J.; Hodges, Kevin I.

2018-04-01

Cyclones play an important role in the coupled dynamics of the Arctic climate system on a range of time scales. Modeling studies suggest that storminess will increase in Arctic summer due to enhanced land-sea thermal contrast along the Arctic coastline, in a region known as the Arctic Frontal Zone (AFZ). However, the climate models used in these studies are poor at reproducing the present-day Arctic summer cyclone climatology and so their projections of Arctic cyclones and related quantities, such as sea ice, may not be reliable. In this study we perform composite analysis of Arctic cyclone statistics using AFZ variability as an analog for climate change. High AFZ years are characterized both by increased cyclone frequency and dynamical intensity, compared to low years. Importantly, the size of the response in this analog suggests that General Circulation Models may underestimate the response of Arctic cyclones to climate change, given a similar change in baroclinicity.

Global Precipitation Measurement, Validation, and Applications Integrated Hydrologic Validation to Improve Physical Precipitation Retrievals for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidar, Christa D.; Tian, Yudong; Kenneth, Tian; Harrison, Kenneth; Kumar, Sujay

2011-01-01

Land surface modeling and data assimilation can provide dynamic land surface state variables necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in the Global Precipitation Measurement Mission (GPM), is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. In order to investigate the robustness of both the land surface model states and the microwave emissivity and forward radiative transfer models, we have undertaken a multi-site investigation as part of the NASA Precipitation Measurement Missions (PMM) Land Surface Characterization Working Group. Specifically, we will demonstrate the performance of the Land Information System (LIS; http://lis.gsfc.nasa.gov; Peters-Lidard et aI., 2007; Kumar et al., 2006) coupled to the Joint Center for Satellite Data Assimilation (JCSDA's) Community Radiative Transfer Model (CRTM; Weng, 2007; van Deist, 2009). The land surface is characterized by complex physical/chemical constituents and creates temporally and spatially heterogeneous surface properties in response to microwave radiation scattering. The uncertainties in surface microwave emission (both surface radiative temperature and emissivity) and very low polarization ratio are linked to difficulties in rainfall detection using low-frequency passive microwave sensors (e.g.,Kummerow et al. 2001). Therefore, addressing these issues is of utmost importance for the GPM mission. There are many approaches to parameterizing land surface emission and radiative transfer, some of which have been customized for snow (e.g., the Helsinki University of Technology or HUT radiative transfer model;) and soil moisture (e.g., the Land Surface Microwave Emission Model or LSMEM).

Large uncertainty in carbon uptake potential of land-based climate-change mitigation efforts.

PubMed

Krause, Andreas; Pugh, Thomas A M; Bayer, Anita D; Li, Wei; Leung, Felix; Bondeau, Alberte; Doelman, Jonathan C; Humpenöder, Florian; Anthoni, Peter; Bodirsky, Benjamin L; Ciais, Philippe; Müller, Christoph; Murray-Tortarolo, Guillermo; Olin, Stefan; Popp, Alexander; Sitch, Stephen; Stehfest, Elke; Arneth, Almut

2018-07-01

Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land-based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land-based mitigation scenarios from two land-use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ-GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land-use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land-use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land-use change. Differences between land-use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land-based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy. © 2018 John Wiley & Sons Ltd.

The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use

NASA Astrophysics Data System (ADS)

Souty, F.; Brunelle, T.; Dumas, P.; Dorin, B.; Ciais, P.; Crassous, R.; Müller, C.; Bondeau, A.

2012-02-01

Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. The land-use modelling approach described in this paper entails several advantages. Firstly, it makes it possible to explore interactions among different types of biomass demand for food and animal feed, in a consistent approach, including indirect effects on land-use change resulting from international trade. Secondly, yield variations induced by the possible expansion of croplands on less suitable marginal lands are modelled by using regional land area distributions of potential yields, and a calculated boundary between intensive and extensive production. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.

Ditching Tests of a 1/18-Scale Model of the Lockheed Constellation Airplane

NASA Technical Reports Server (NTRS)

Fisher, Lloyd J.; Morris, Garland J.

1948-01-01

Tests were made of a 1/18-scale dynamically similar model of the Lockheed Constellation airplane to investigate its ditching characteristics and proper ditching technique. Scale-strength bottoms were used to reproduce probable damage to the fuselage. The model was landed in calm water at the Langley tank no. 2 monorail. Various landing attitudes, speeds, and fuselage configuration were simulated. The behavior of the model was determined from visual observations, by recording the longitudinal decelerations, and by taking motion pictures of the ditchings. Data are presented in tabular form, sequence photographs, and time-history deceleration curves. It was concluded that the airplane should be ditched at a medium nose-high landing attitude with the landing flaps full down. The airplane will probably make a deep run with heavy spray and may even dive slightly. The fuselage will be damaged and leak substantially but in calm water probably will not flood rapidly. Maximum longitudinal decelerations in a calm-water ditching will be about 4g.

The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use

NASA Astrophysics Data System (ADS)

Souty, F.; Brunelle, T.; Dumas, P.; Dorin, B.; Ciais, P.; Crassous, R.; Müller, C.; Bondeau, A.

2012-10-01

Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.

Development and Implementation of the DTOPLATS-MP land surface model over the Continental US at 30 meters

NASA Astrophysics Data System (ADS)

Chaney, N.; Wood, E. F.

2014-12-01

The increasing accessibility of high-resolution land data (< 100 m) and high performance computing allows improved parameterizations of subgrid hydrologic processes in macroscale land surface models. Continental scale fully distributed modeling at these spatial scales is possible; however, its practicality for operational use is still unknown due to uncertainties in input data, model parameters, and storage requirements. To address these concerns, we propose a modeling framework that provides the spatial detail of a fully distributed model yet maintains the benefits of a semi-distributed model. In this presentation we will introduce DTOPLATS-MP, a coupling between the NOAH-MP land surface model and the Dynamic TOPMODEL hydrologic model. This new model captures a catchment's spatial heterogeneity by clustering high-resolution land datasets (soil, topography, and land cover) into hundreds of hydrologic similar units (HSUs). A prior DEM analysis defines the connections between each HSU. At each time step, the 1D land surface model updates each HSU; the HSUs then interact laterally via the subsurface and surface. When compared to the fully distributed form of the model, this framework allows a significant decrease in computation and storage while providing most of the same information and enabling parameter transferability. As a proof of concept, we will show how this new modeling framework can be run over CONUS at a 30-meter spatial resolution. For each catchment in the WBD HUC-12 dataset, the model is run between 2002 and 2012 using available high-resolution continental scale land and meteorological datasets over CONUS (dSSURGO, NLCD, NED, and NCEP Stage IV). For each catchment, the model is run with 1000 model parameter sets obtained from a Latin hypercube sample. This exercise will illustrate the feasibility of running the model operationally at continental scales while accounting for model parameter uncertainty.

Modeling temperature and humidity profiles within forest canopies

USDA-ARS?s Scientific Manuscript database

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

LONG-TERM PROJECTIONS OF EASTERN OYSTER POPULATIONS UNDER VARIOUS MANAGEMENT SCENARIOS

EPA Science Inventory

Time series of fishery-dependent and fishery-independent data were used to parameterize a model of oyster population dynamics for Maryland's Chesapeake Bay. Model parameters are (1) fishing mortality, estimated from differences between predicted and reported landings scaled to a ...

Climatic and anthropogenic forcing of prehistorical vegetation succession and fire dynamics in the Lago di Como area (N-Italy, Insubria)

NASA Astrophysics Data System (ADS)

Martinelli, Elisa; Michetti, Alessandro Maria; Colombaroli, Daniele; Mazzola, Eleonora; Motella De Carlo, Sila; Livio, Franz; Gilli, Adrian; Ferrario, Maria Francesca; Höbig, Nicole; Brunamonte, Fabio; Castelletti, Lanfredo; Tinner, Willy

2017-04-01

Combined pollen, charcoal and modeling evidence from the Insubria Region suggests that fire was a major driver of late Holocene vegetation change. However, the extent and timing of fire response dynamics are not clear yet. We use lacustrine sediments from Lago di Como (N-Italy, S-Alps) to assess if the reconstructed vegetation and fire dynamics were relevant at large scales and if they coincided in time with those observed at smaller sites. The lake, due to its size (142 km2) and economic potential, was very attractive for early land use and human presence in this area is well documented since ca. 10,000 yrs ago (Mesolithic). We used pollen, plant macrofossils and charcoal to reconstruct the vegetation composition and fire activity. During the Younger Dryas and the Early Holocene until ca. 8000 cal BP natural dynamics prevailed. Subsequently, land use and slash-and-burn activities increased at the Mesolithic-Neolithic transition and became widespread around ca. 6500 cal BP. Microscopic charcoal and numerical analyses demonstrate that anthropogenic fires had a determinant influence on long-term vegetation dynamics at regional scales in Insubria. Microscopic charcoal and pollen and spores indicative of land use show that human pressure intensified after ca. 5300 cal yr BP and even more since ca. 4300 cal yr BP. Our results suggest that important species which disappeared or were strongly reduced by land use and fire (e.g. Abies alba, Tilia, Ulmus) will potentially reestablish in the Lago di Como area and elsewhere in Insubria, if land abandonment initiated in the 1950s will continue.

Representing Northern Peatland Hydrology and Biogeochemistry with ALM Land Surface Model

NASA Astrophysics Data System (ADS)

Shi, X.; Ricciuto, D. M.; Thornton, P. E.; Hanson, P. J.; Xu, X.; Mao, J.; Warren, J.; Yuan, F.; Norby, R. J.; Sebestyen, S.; Griffiths, N.; Weston, D. J.; Walker, A.

2017-12-01

Northern peatlands are likely to be important in future carbon cycle-climate feedbacks due to their large carbon pool and vulnerability to hydrological change. Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth for a vegetated wetland, independent of prescribed regional water tables. Firstly, we introduce a new configuration of the land model (ALM) of Accelerated Climate model for Energy (ACME), which includes a fully prognostic water table calculation for a vegetated peatland. Secondly, we couple our new hydrology treatment with vertically structured soil organic matter pool, and the addition of components from methane biogeochemistry. Thirdly, we introduce a new PFT for mosses and implement the water content dynamics and physiology of mosses. We inform and test our model based on SPRUCE experiment to get the reasonable results for the seasonal dynamics water table depths, water content dynamics and physiology of mosses, and correct soil carbon profiles. Then, we use our new model structure to test the how the water table depth and CH4 emission will respond to elevated CO2 and different warming scenarios.

Flight Investigation of the Stability and Control Characteristics of a 1/4-Scale Model of a Tilt-Wing Vertical-Take-Off-and-Landing Aircraft

NASA Technical Reports Server (NTRS)

Tosti, Louis P.

1959-01-01

An experimental investigation has been conducted to determine the dynamic stability and control characteristics of a tilt-wing vertical-take-off-and-landing aircraft with the use of a remotely controlled 1/4-scale free-flight model. The model had two propellers with hinged (flapping) blades mounted on the wing which could be tilted up to an incidence angle of nearly 90 deg for vertical take-off and landing. The investigation consisted of hovering flights in still air, vertical take-offs and landings, and slow constant-altitude transitions from hovering to forward flight. The stability and control characteristics of the model were generally satisfactory except for the following characteristics. In hovering flight, the model had an unstable pitching oscillation of relatively long period which the pilots were able to control without artificial stabilization but which could not be considered entirely satisfactory. At very low speeds and angles of wing incidence on the order of 70 deg, the model experienced large nose-up pitching moments which severely limited the allowable center-of-gravity range.

Response to droughts and heat waves of the productivity of natural and agricultural ecosystems in Europe within ISI-MIP2 historical simulations

NASA Astrophysics Data System (ADS)

François, Louis; Henrot, Alexandra-Jane; Dury, Marie; Jacquemin, Ingrid; Munhoven, Guy; Friend, Andrew; Rademacher, Tim T.; Hacket Pain, Andrew J.; Hickler, Thomas; Tian, Hanqin; Morfopoulos, Catherine; Ostberg, Sebastian; Chang, Jinfeng; Rafique, Rashid; Nishina, Kazuya

2016-04-01

According to the projections of climate models, extreme events such as droughts and heat waves are expected to become more frequent and more severe in the future. Such events are known to severely impact the productivity of both natural and agricultural ecosystems, and hence to affect ecosystem services such as crop yield and ecosystem carbon sequestration potential. Dynamic vegetation models are conventional tools to evaluate the productivity and carbon sequestration of ecosystems and their response to climate change. However, how far are these models able to correctly represent the sensitivity of ecosystems to droughts and heat waves? How do the responses of natural and agricultural ecosystems compare to each other, in terms of drought-induced changes in productivity and carbon sequestration? In this contribution, we use ISI-MIP2 model historical simulations from the biome sector to tentatively answer these questions. Nine dynamic vegetation models have participated in the biome sector intercomparison of ISI-MIP2: CARAIB, DLEM, HYBRID, JULES, LPJ-GUESS, LPJml, ORCHIDEE, VEGAS and VISIT. We focus the analysis on well-marked droughts or heat waves that occured in Europe after 1970, such as the 1976, 2003 and 2010 events. For most recent studied events, the model results are compared to the response observed at several eddy covariance sites in Europe, and, at a larger scale, to the changes in crop productivities reported in national statistics or to the drought impacts on gross primary productivity derived from satellite data (Terra MODIS instrument). The sensitivity of the models to the climatological dataset used in the simulations, as well as to the inclusion or not of anthropogenic land use, is also analysed within the studied events. Indeed, the ISI-MIP simulations have been run with four different historical climatic forcings, as well as for several land use/land cover configurations (natural vegetation, fixed land use and variable land use).

Trade-offs between maintenance of ecosystem services and socio-economic development in rural mountainous communities in southern Spain: a dynamic simulation approach.

PubMed

Vidal-Legaz, Beatriz; Martínez-Fernández, Julia; Picón, Andrés Sánchez; Pugnaire, Francisco I

2013-12-15

Mountainous rural communities have traditionally managed their land extensively, resulting in land uses that provide important ecosystem services for both rural and urban areas. Over recent decades, these communities have undergone drastic changes in economic structure, population size and land use. Our understanding of the exact mechanisms that drive these changes is limited, and there is also a lack of integrative approaches to enable decision makers to steer rural development towards a more sustainable path. In this study, we build a dynamic simulation model to calculate the trade-offs between the provisions of two ecosystem services - landscape aesthetic value and water supply for human use - and the economic development associated with different land use changes. The study area for the simulation comprises two rural communities located in southern Spain. Our results show trade-offs between economic development and the provision of the selected ecosystem services in the selected study area. Land use intensification results in economic development but is not enough to prevent population loss and has a negative impact on both the water supply and on aesthetic services. We conclude that more proactive management policies are needed to mitigate a loss in ecosystem services. Simulation models like ours may facilitate the choice of these policies, as they could test the result of land use planning policies contributing therefore, to a more integrative and sustainable management of rural communities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effects of surrounding land use and water depth on seagrass dynamics relative to a catastrophic algal bloom.

PubMed

Breininger, David R; Breininger, Robert D; Hall, Carlton R

2017-02-01

Seagrasses are the foundation of many coastal ecosystems and are in global decline because of anthropogenic impacts. For the Indian River Lagoon (Florida, U.S.A.), we developed competing multistate statistical models to quantify how environmental factors (surrounding land use, water depth, and time [year]) influenced the variability of seagrass state dynamics from 2003 to 2014 while accounting for time-specific detection probabilities that quantified our ability to determine seagrass state at particular locations and times. We classified seagrass states (presence or absence) at 764 points with geographic information system maps for years when seagrass maps were available and with aerial photographs when seagrass maps were not available. We used 4 categories (all conservation, mostly conservation, mostly urban, urban) to describe surrounding land use within sections of lagoonal waters, usually demarcated by land features that constricted these waters. The best models predicted that surrounding land use, depth, and year would affect transition and detection probabilities. Sections of the lagoon bordered by urban areas had the least stable seagrass beds and lowest detection probabilities, especially after a catastrophic seagrass die-off linked to an algal bloom. Sections of the lagoon bordered by conservation lands had the most stable seagrass beds, which supports watershed conservation efforts. Our results show that a multistate approach can empirically estimate state-transition probabilities as functions of environmental factors while accounting for state-dependent differences in seagrass detection probabilities as part of the overall statistical inference procedure. © 2016 Society for Conservation Biology.

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

The Influence of Agroforestry and Other Land-Use Types on the Persistence of a Sumatran Tiger ( Panthera tigris sumatrae) Population: An Individual-Based Model Approach

NASA Astrophysics Data System (ADS)

Imron, Muhammad Ali; Herzog, Sven; Berger, Uta

2011-08-01

The importance of preserving both protected areas and their surrounding landscapes as one of the major conservation strategies for tigers has received attention over recent decades. However, the mechanism of how land-use surrounding protected areas affects the dynamics of tiger populations is poorly understood. We developed Panthera Population Persistence (PPP)—an individual-based model—to investigate the potential mechanism of the Sumatran tiger population dynamics in a protected area and under different land-use scenarios surrounding the reserve. We tested three main landscape compositions (single, combined and real land-uses of Tesso-Nilo National Park and its surrounding area) on the probability of and time to extinction of the Sumatran tiger over 20 years in Central Sumatra. The model successfully explains the mechanisms behind the population response of tigers under different habitat landscape compositions. Feeding and mating behaviours of tigers are key factors, which determined population persistence in a heterogeneous landscape. All single land-use scenarios resulted in tiger extinction but had a different probability of extinction within 20 years. If tropical forest was combined with other land-use types, the probability of extinction was smaller. The presence of agroforesty and logging concessions adjacent to protected areas encouraged the survival of tiger populations. However, with the real land-use scenario of Tesso-Nilo National Park, tigers could not survive for more than 10 years. Promoting the practice of agroforestry systems surrounding the park is probably the most reasonable way to steer land-use surrounding the Tesso-Nilo National Park to support tiger conservation.

Modeled impact of anthropogenic land cover change on climate

USGS Publications Warehouse

Findell, K.L.; Shevliakova, E.; Milly, P.C.D.; Stouffer, R.J.

2007-01-01

Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory's climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation. ?? 2007 American Meteorological Society.

System identification methods for aircraft flight control development and validation

NASA Technical Reports Server (NTRS)

Tischler, Mark B.

1995-01-01

System-identification methods compose a mathematical model, or series of models, from measurements of inputs and outputs of dynamic systems. The extracted models allow the characterization of the response of the overall aircraft or component subsystem behavior, such as actuators and on-board signal processing algorithms. This paper discusses the use of frequency-domain system-identification methods for the development and integration of aircraft flight-control systems. The extraction and analysis of models of varying complexity from nonparametric frequency-responses to transfer-functions and high-order state-space representations is illustrated using the Comprehensive Identification from FrEquency Responses (CIFER) system-identification facility. Results are presented for test data of numerous flight and simulation programs at the Ames Research Center including rotorcraft, fixed-wing aircraft, advanced short takeoff and vertical landing (ASTOVL), vertical/short takeoff and landing (V/STOL), tiltrotor aircraft, and rotor experiments in the wind tunnel. Excellent system characterization and dynamic response prediction is achieved for this wide class of systems. Examples illustrate the role of system-identification technology in providing an integrated flow of dynamic response data around the entire life-cycle of aircraft development from initial specifications, through simulation and bench testing, and into flight-test optimization.

Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago

PubMed Central

Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E.

2018-01-01

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns. PMID:29657753

Comparing spatial diversification and meta-population models in the Indo-Australian Archipelago.

PubMed

Chalmandrier, Loïc; Albouy, Camille; Descombes, Patrice; Sandel, Brody; Faurby, Soren; Svenning, Jens-Christian; Zimmermann, Niklaus E; Pellissier, Loïc

2018-03-01

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns.

Interactions between nitrogen deposition, land cover conversion, and climate change determine the contemporary carbon balance of Europe

NASA Astrophysics Data System (ADS)

Churkina, G.; Zaehle, S.; Hughes, J.; Viovy, N.; Chen, Y.; Jung, M.; Heumann, B. W.; Ramankutty, N.; Heimann, M.; Jones, C.

2010-09-01

European ecosystems are thought to take up large amounts of carbon, but neither the rate nor the contributions of the underlying processes are well known. In the second half of the 20th century, carbon dioxide concentrations have risen by more that 100 ppm, atmospheric nitrogen deposition has more than doubled, and European mean temperatures were increasing by 0.02 °C yr-1. The extents of forest and grasslands have increased with the respective rates of 5800 km2 yr-1 and 1100 km2 yr-1 as agricultural land has been abandoned at a rate of 7000 km2 yr-1. In this study, we analyze the responses of European land ecosystems to the aforementioned environmental changes using results from four process-based ecosystem models: BIOME-BGC, JULES, ORCHIDEE, and O-CN. The models suggest that European ecosystems sequester carbon at a rate of 56 TgC yr-1 (mean of four models for 1951-2000) with strong interannual variability (±88 TgC yr-1, average across models) and substantial inter-model uncertainty (±39 TgC yr-1). Decadal budgets suggest that there has been a continuous increase in the mean net carbon storage of ecosystems from 85 TgC yr-1 in 1980s to 108 TgC yr-1 in 1990s, and to 114 TgC yr-1 in 2000-2007. The physiological effect of rising CO2 in combination with nitrogen deposition and forest re-growth have been identified as the important explanatory factors for this net carbon storage. Changes in the growth of woody vegetation are suggested as an important contributor to the European carbon sink. Simulated ecosystem responses were more consistent for the two models accounting for terrestrial carbon-nitrogen dynamics than for the two models which only accounted for carbon cycling and the effects of land cover change. Studies of the interactions of carbon-nitrogen dynamics with land use changes are needed to further improve the quantitative understanding of the driving forces of the European land carbon balance.

Linking state-and-transition simulation and timber supply models for forest biomass production scenarios

USGS Publications Warehouse

Costanza, Jennifer; Abt, Robert C.; McKerrow, Alexa; Collazo, Jaime

2015-01-01

We linked state-and-transition simulation models (STSMs) with an economics-based timber supply model to examine landscape dynamics in North Carolina through 2050 for three scenarios of forest biomass production. Forest biomass could be an important source of renewable energy in the future, but there is currently much uncertainty about how biomass production would impact landscapes. In the southeastern US, if forests become important sources of biomass for bioenergy, we expect increased land-use change and forest management. STSMs are ideal for simulating these landscape changes, but the amounts of change will depend on drivers such as timber prices and demand for forest land, which are best captured with forest economic models. We first developed state-and-transition model pathways in the ST-Sim software platform for 49 vegetation and land-use types that incorporated each expected type of landscape change. Next, for the three biomass production scenarios, the SubRegional Timber Supply Model (SRTS) was used to determine the annual areas of thinning and harvest in five broad forest types, as well as annual areas converted among those forest types, agricultural, and urban lands. The SRTS output was used to define area targets for STSMs in ST-Sim under two scenarios of biomass production and one baseline, business-as-usual scenario. We show that ST-Sim output matched SRTS targets in most cases. Landscape dynamics results indicate that, compared with the baseline scenario, forest biomass production leads to more forest and, specifically, more intensively managed forest on the landscape by 2050. Thus, the STSMs, informed by forest economics models, provide important information about potential landscape effects of bioenergy production.

Uncertainties in the land-use flux resulting from land-use change reconstructions and gross land transitions

NASA Astrophysics Data System (ADS)

Bayer, Anita D.; Lindeskog, Mats; Pugh, Thomas A. M.; Anthoni, Peter M.; Fuchs, Richard; Arneth, Almut

2017-02-01

Land-use and land-cover (LUC) changes are a key uncertainty when attributing changes in measured atmospheric CO2 concentration to its sinks and sources and must also be much better understood to determine the possibilities for land-based climate change mitigation, especially in the light of human demand on other land-based resources. On the spatial scale typically used in terrestrial ecosystem models (0.5 or 1°) changes in LUC over time periods of a few years or more can include bidirectional changes on the sub-grid level, such as the parallel expansion and abandonment of agricultural land (e.g. in shifting cultivation) or cropland-grassland conversion (and vice versa). These complex changes between classes within a grid cell have often been neglected in previous studies, and only net changes of land between natural vegetation cover, cropland and pastures accounted for, mainly because of a lack of reliable high-resolution historical information on gross land transitions, in combination with technical limitations within the models themselves. In the present study we applied a state-of-the-art dynamic global vegetation model with a detailed representation of croplands and carbon-nitrogen dynamics to quantify the uncertainty in terrestrial ecosystem carbon stocks and fluxes arising from the choice between net and gross representations of LUC. We used three frequently applied global, one recent global and one recent European LUC datasets, two of which resolve gross land transitions, either in Europe or in certain tropical regions. When considering only net changes, land-use-transition uncertainties (expressed as 1 standard deviation around decadal means of four models) in global carbon emissions from LUC (ELUC) are ±0.19, ±0.66 and ±0.47 Pg C a-1 in the 1980s, 1990s and 2000s, respectively, or between 14 and 39 % of mean ELUC. Carbon stocks at the end of the 20th century vary by ±11 Pg C for vegetation and ±37 Pg C for soil C due to the choice of LUC reconstruction, i.e. around 3 % of the respective C pools. Accounting for sub-grid (gross) land conversions significantly increased the effect of LUC on global and European carbon stocks and fluxes, most noticeably enhancing global cumulative ELUC by 33 Pg C (1750-2014) and entailing a significant reduction in carbon stored in vegetation, although the effect on soil C stocks was limited. Simulations demonstrated that assessments of historical carbon stocks and fluxes are highly uncertain due to the choice of LUC reconstruction and that the consideration of different contrasting LUC reconstructions is needed to account for this uncertainty. The analysis of gross, in addition to net, land-use changes showed that the full complexity of gross land-use changes is required in order to accurately predict the magnitude of LUC change emissions. This introduces technical challenges to process-based models and relies on extensive information regarding historical land-use transitions.

A modeling technique for STOVL ejector and volume dynamics

NASA Technical Reports Server (NTRS)

Drummond, C. K.; Barankiewicz, W. S.

1990-01-01

New models for thrust augmenting ejector performance prediction and feeder duct dynamic analysis are presented and applied to a proposed Short Take Off and Vertical Landing (STOVL) aircraft configuration. Central to the analysis is the nontraditional treatment of the time-dependent volume integrals in the otherwise conventional control-volume approach. In the case of the thrust augmenting ejector, the analysis required a new relationship for transfer of kinetic energy from the primary flow to the secondary flow. Extraction of the required empirical corrections from current steady-state experimental data is discussed; a possible approach for modeling insight through Computational Fluid Dynamics (CFD) is presented.

Using Flux Site Observations to Calibrate Root System Architecture Stencils for Water Uptake of Plant Functional Types in Land Surface Models.

NASA Astrophysics Data System (ADS)

Bouda, M.

2017-12-01

Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, RSA has not been included because of its three-dimensional complexity, which makes RSA modelling generally too computationally costly. This work builds upon the recently introduced "RSA stencil," a process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA in response to heterogeneous soil moisture profiles. In validations using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, the RSA stencil predicts plant water potentials within 2% of the outputs of full 3D models, despite its trivial computational cost. In transient simulations, the RSA stencil yields improved predictions of water uptake and soil moisture profiles compared to a 1D model based on root fraction alone. Here I show how the RSA stencil can be calibrated to time-series observations of soil moisture and transpiration to yield a water uptake PFT definition for use in terrestrial models. This model-data integration exercise aims to improve LSM predictions of soil moisture dynamics and, under water-limiting conditions, surface fluxes. These improvements can be expected to significantly impact predictions of downstream variables, including surface fluxes, climate-vegetation feedbacks and soil nutrient cycling.

Theory Can Help Structure Regression Models for Projecting Stream Conditions Under Alternative Land Use Scenarios

NASA Astrophysics Data System (ADS)

van Sickle, J.; Baker, J.; Herlihy, A.

2005-05-01

We built multiple regression models for Emphemeroptera/ Plecoptera/ Tricoptera (EPT) taxon richness and other indicators of biological condition in streams of the Willamette River Basin, Oregon, USA. The models were used to project the changes in condition that would be expected in all 2-4th order streams of the 30000 sq km basin under alternative scenarios of future land use. In formulating the models, we invoked the theory of limiting factors to express the interactive effects of stream power and watershed land use on EPT richness. The resulting models were parsimonious, and they fit the data in our wedge-shaped scatterplots slightly better than did a naive additive-effects model. Just as theory helped formulate our regression models, the models in turn helped us identify a new research need for the Basin's streams. Our future scenarios project that conversions of agricultural to urban uses may dominate landscape dynamics in the basin over the next 50 years. But our models could not detect any difference between the effects of agricultural and urban development in watersheds on stream biota. This result points to an increased need for understanding how agricultural and urban land uses in the Basin differentially influence stream ecosystems.

Flight Test of L1 Adaptive Control Law: Offset Landings and Large Flight Envelope Modeling Work

NASA Technical Reports Server (NTRS)

Gregory, Irene M.; Xargay, Enric; Cao, Chengyu; Hovakimyan, Naira

2011-01-01

This paper presents new results of a flight test of the L1 adaptive control architecture designed to directly compensate for significant uncertain cross-coupling in nonlinear systems. The flight test was conducted on the subscale turbine powered Generic Transport Model that is an integral part of the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. The results presented include control law evaluation for piloted offset landing tasks as well as results in support of nonlinear aerodynamic modeling and real-time dynamic modeling of the departure-prone edges of the flight envelope.

Regional Eco-hydrologic Sensitivity to Projected Amazonian Land Use Scenarios

NASA Astrophysics Data System (ADS)

Knox, R. G.; Longo, M.; Zhang, K.; Levine, N. M.; Moorcroft, P. R.; Bras, R. L.

2011-12-01

Given business as usual land-use practices, it is estimated that by 2050 roughly half of the Amazon's pre-anthropogenic closed-canopy forest stands would remain. Of this, eight of the Amazon's twelve major hydrologic basins would lose more than half of their forest cover to deforestation. With the availability of these land-use projections, we may start to question the associated response of the region's hydrologic climate to significant land-cover change. Here the Ecosystem-Demography Model 2 (EDM2, a dynamic and spatially distributed terrestrial model of plant structure and composition, succession, disturbance and thermodynamic transfer) is coupled with the Brazilian Regional Atmospheric Model (BRAMS, a three-dimensional limited area model of the atmospheric fluid momentum equations and physics parameterizations for closing the system of equations at the lower boundary, convection, radiative transfer, microphysics, etc). This experiment conducts decadal simulations, framed with high-reliability lateral boundary conditions of reanalysis atmospheric data (ERA-40 interim) and variable impact of land-use scenarios (SimAmazonia). This is done by initializing the regional ecosystem structure with both aggressive and conservationist deforestation scenarios, and also by differentially allowing and not-allowing dynamic vegetation processes. While the lateral boundaries of the simulation will not reflect the future climate in the region, reanalysis data has provided improved realism as compared to results derived from GCM boundary data. Therefore, the ecosystem response (forest composition and structure) and the time-space patterns of hydrologic information (soil moisture, rainfall, evapotranspiration) are objectively compared in the context of a sensitivity experiment, as opposed to a forecast. The following questions are addressed. How do aggressive and conservative scenarios of Amazonian deforestation effect the regional patterning of hydrologic information in the Amazon and South American Convergence Zone, and does forest response in these regions influence that patterning of hydrologic information?

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.

Chapter 2: Dynamic vegetation modeling of forest, woodland, shrubland, and grassland vegetation communities in the Pacific Northwest and Southwest Regions of the United States

Treesearch

Theresa K. Burcsu; Joshua S. Halofsky; Simon A. Bisrat; Treg A. Christopher; Megan K. Creutzburg; Emilie B. Henderson; Miles A. Hemstrom; F. Jack Triepke; Melissa Whitman

2014-01-01

Land management planning at broad scales requires integrative techniques to understand and synthesize the effects of different land management activities and address socioeconomic and conservation concerns. The Integrated Landscape Assessment Project was developed to support the vital but complex task of broadscale integration of information to assess ecological...

Tire/runway friction interface

NASA Technical Reports Server (NTRS)

Yager, Thomas J.

1990-01-01

An overview is given of NASA Langley's tire/runway pavement interface studies. The National Tire Modeling Program, evaluation of new tire and landing gear designs, tire wear and friction tests, and tire hydroplaning studies are examined. The Aircraft Landing Dynamics Facility is described along with some ground friction measuring vehicles. The major goals and scope of several joint FAA/NASA programs are identified together with current status and plans.

Land use and carbon dynamics in the southeastern United States from 1992 to 2050

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Sohl, Terry L.; Young, Claudia; Werner, Jeremy M.

2013-01-01

Land use and land cover change (LUCC) plays an important role in determining the spatial distribution, magnitude, and temporal change of terrestrial carbon sources and sinks. However, the impacts of LUCC are not well understood and quantified over large areas. The goal of this study was to quantify the spatial and temporal patterns of carbon dynamics in various terrestrial ecosystems in the southeastern United States from 1992 to 2050 using a process-based modeling system and then to investigate the impacts of LUCC. Spatial LUCC information was reconstructed and projected using the FOREcasting SCEnarios of future land cover (FORE-SCE) model according to information derived from Landsat observations and other sources. Results indicated that urban expansion (from 3.7% in 1992 to 9.2% in 2050) was expected to be the primary driver for other land cover changes in the region, leading to various declines in forest, cropland, and hay/pasture. The region was projected to be a carbon sink of 60.4 gC m−2 yr−1 on average during the study period, primarily due to the legacy impacts of large-scale conversion of cropland to forest that happened since the 1950s. Nevertheless, the regional carbon sequestration rate was expected to decline because of the slowing down of carbon accumulation in aging forests and the decline of forest area.

Transient simulations of historical climate change including interactive carbon emissions from land-use change.

NASA Astrophysics Data System (ADS)

Matveev, A.; Matthews, H. D.

2009-04-01

Carbon fluxes from land conversion are among the most uncertain variables in our understanding of the contemporary carbon cycle, which limits our ability to estimate both the total human contribution to current climate forcing and the net effect of terrestrial biosphere changes on atmospheric CO2 increases. The current generation of coupled climate-carbon models have made significant progress in simulating the coupled climate and carbon cycle response to anthropogenic CO2 emissions, but do not typically include land-use change as a dynamic component of the simulation. In this work we have incorporated a book-keeping land-use carbon accounting model into the University of Victoria Earth System Climate Model (UVic ESCM), and intermediate-complexity coupled climate-carbon model. The terrestrial component of the UVic ESCM allows an aerial competition of five plant functional types (PFTs) in response to climatic conditions and area availability, and tracks the associated changes in affected carbon pools. In order to model CO2 emissions from land conversion in the terrestrial component of the model, we calculate the allocation of carbon to short and long-lived wood products following specified land-cover change, and use varying decay timescales to estimate CO2 emissions. We use recently available spatial datasets of both crop and pasture distributions to drive a series of transient simulations and estimate the net contribution of human land-use change to historical carbon emissions and climate change.

Soil carbon management in large-scale Earth system modelling: implications for crop yields and nitrogen leaching

NASA Astrophysics Data System (ADS)

Olin, S.; Lindeskog, M.; Pugh, T. A. M.; Schurgers, G.; Wårlind, D.; Mishurov, M.; Zaehle, S.; Stocker, B. D.; Smith, B.; Arneth, A.

2015-06-01

We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land use-enabled dynamic vegetation model LPJ-GUESS. Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. We explore trade-offs between important ecosystem services that can be provided from agricultural fields such as crop yields, retention of nitrogen and carbon storage. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till and cover-crops proposed in literature is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C-N interactions in agricultural ecosystems under future environmental change, and the effects these have on terrestrial biogeochemical cycles.

Outlook on a worldwide forest transition.

PubMed

Pagnutti, Chris; Bauch, Chris T; Anand, Madhur

2013-01-01

It is not clear whether a worldwide "forest transition" to net reforestation will ever occur, and the need to address the main driver--agriculture--is compelling. We present a mathematical model of land use dynamics based on the world food equation that explains historical trends in global land use on the millennial scale. The model predicts that a global forest transition only occurs under a small and very specific range of parameter values (and hence seems unlikely) but if it does occur, it would have to occur within the next 70 years. In our baseline scenario, global forest cover continues to decline until it stabilizes within the next two centuries at 22% of global land cover, and wild pasture at 1.4%. Under other scenarios the model predicts unanticipated dynamics wherein a forest transition may relapse, heralding a second era of deforestation; this brings into question national-level forest transitions observed in recent decades, and suggests we need to expand our lexicon of possibilities beyond the simple "forest transition/no forest transition" dichotomy. This research also underscores that the challenge of feeding a growing population while conserving natural habitat will likely continue for decades to come.

A Simple Exploration of Complexity at the Climate-Weather-Social-Conflict Nexus

NASA Astrophysics Data System (ADS)

Shaw, M.

2017-12-01

The conceptualization, exploration, and prediction of interplay between climate, weather, important resources, and social and economic - so political - human behavior is cast, and analyzed, in terms familiar from statistical physics and nonlinear dynamics. A simple threshold toy model is presented which emulates human tendencies to either actively engage in responses deriving, in part, from environmental circumstances or to maintain some semblance of status quo, formulated based on efforts drawn from the sociophysics literature - more specifically vis a vis a model akin to spin glass depictions of human behavior - with threshold/switching of individual and collective dynamics influenced by relatively more detailed weather and land surface model (hydrological) analyses via a land data assimilation system (a custom rendition of the NASA GSFC Land Information System). Parameters relevant to human systems' - e.g., individual and collective switching - sensitivity to hydroclimatology are explored towards investigation of overall system behavior; i.e., fixed points/equilibria, oscillations, and bifurcations of systems composed of human interactions and responses to climate and weather through, e.g., agriculture. We discuss implications in terms of conceivable impacts of climate change and associated natural disasters on socioeconomics, politics, and power transfer, drawing from relatively recent literature concerning human conflict.

Regional-Scale Modeling at NASA Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Adler, R.; Baker, D.; Braun, S.; Chou, M.-D.; Jasinski, M. F.; Jia, Y.; Kakar, R.; Karyampudi, M.; Lang, S.

2003-01-01

Over the past decade, the Goddard Mesoscale Modeling and Dynamics Group has used a popular regional scale model, MM5, to study precipitation processes. Our group is making contributions to the MM5 by incorporating the following physical and numerical packages: improved Goddard cloud processes, a land processes model (Parameterization for Land-Atmosphere-Cloud Exchange - PLACE), efficient but sophisticated radiative processes, conservation of hydrometeor mass (water budget), four-dimensional data assimilation for rainfall, and better computational methods for trace gas transport. At NASA Goddard, the MM5 has been used to study: (1) the impact of initial conditions, assimilation of satellite-derived rainfall, and cumulus parameterizations on rapidly intensifying oceanic cyclones, hurricanes and typhoons, (2) the dynamic and thermodynamic processes associated with the development of narrow cold frontal rainbands, (3) regional climate and water cycles, (4) the impact of vertical transport by clouds and lightning on trace gas distributiodproduction associated with South and North American mesoscale convective systems, (5) the development of a westerly wind burst (WWB) that occurred during the TOGA COARE and the diurnal variation of precipitation in the tropics, (6) a Florida sea breeze convective event and a Mid-US flood event using a sophisticated land surface model, (7) the influence of soil heterogeneity on land surface energy balance in the southwest GCIP region, (8) explicit simulations (with 1.33 to 4 km horizontal resolution) of hurricanes Bob (1991) and Bonnie (1998), (9) a heavy precipitation event over Taiwan, and (10) to make real time forecasts for a major NASA field program. In this paper, the modifications and simulated cases will be described and discussed.

One carbon cycle: Impacts of model integration, ecosystem process detail, model resolution, and initialization data, on projections of future climate mitigation strategies

NASA Astrophysics Data System (ADS)

Fisk, J.; Hurtt, G. C.; le page, Y.; Patel, P. L.; Chini, L. P.; Sahajpal, R.; Dubayah, R.; Thomson, A. M.; Edmonds, J.; Janetos, A. C.

2013-12-01

Integrated assessment models (IAMs) simulate the interactions between human and natural systems at a global scale, representing a broad suite of phenomena across the global economy, energy system, land-use, and carbon cycling. Most proposed climate mitigation strategies rely on maintaining or enhancing the terrestrial carbon sink as a substantial contribution to restrain the concentration of greenhouse gases in the atmosphere, however most IAMs rely on simplified regional representations of terrestrial carbon dynamics. Our research aims to reduce uncertainties associated with forest modeling within integrated assessments, and to quantify the impacts of climate change on forest growth and productivity for integrated assessments of terrestrial carbon management. We developed the new Integrated Ecosystem Demography (iED) to increase terrestrial ecosystem process detail, resolution, and the utilization of remote sensing in integrated assessments. iED brings together state-of-the-art models of human society (GCAM), spatial land-use patterns (GLM) and terrestrial ecosystems (ED) in a fully coupled framework. The major innovative feature of iED is a consistent, process-based representation of ecosystem dynamics and carbon cycle throughout the human, terrestrial, land-use, and atmospheric components. One of the most challenging aspects of ecosystem modeling is to provide accurate initialization of land surface conditions to reflect non-equilibrium conditions, i.e., the actual successional state of the forest. As all plants in ED have an explicit height, it is one of the few ecosystem models that can be initialized directly with vegetation height data. Previous work has demonstrated that ecosystem model resolution and initialization data quality have a large effect on flux predictions at continental scales. Here we use a factorial modeling experiment to quantify the impacts of model integration, process detail, model resolution, and initialization data on projections of future climate mitigation strategies. We find substantial effects on key integrated assessment projections including the magnitude of emissions to mitigate, the economic value of ecosystem carbon storage, future land-use patterns, food prices and energy technology.

Implementing Dynamic Root Optimization in Noah-MP for Simulating Phreatophytic Root Water Uptake

NASA Astrophysics Data System (ADS)

Wang, Ping; Niu, Guo-Yue; Fang, Yuan-Hao; Wu, Run-Jian; Yu, Jing-Jie; Yuan, Guo-Fu; Pozdniakov, Sergey P.; Scott, Russell L.

2018-03-01

Widely distributed in arid and semiarid regions, phreatophytic roots extend into the saturated zone and extract water directly from groundwater. In this paper, we implemented a vegetation optimality model of root dynamics (VOM-ROOT) in the Noah land surface model with multiparameterization options (Noah-MP LSM) to model the extraction of groundwater through phreatophytic roots at a riparian site with a hyperarid climate (with precipitation of 35 mm/yr) in northwestern China. VOM-ROOT numerically describes the natural optimization of the root profile in response to changes in subsurface water conditions. The coupled Noah-MP/VOM-ROOT model substantially improves the simulation of surface energy and water fluxes, particularly during the growing season, compared to the prescribed static root profile in the default Noah-MP. In the coupled model, more roots are required to grow into the saturated zone to meet transpiration demand when the groundwater level declines over the growing season. The modeling results indicate that at the study site, the modeled annual transpiration is 472 mm, accounting for 92.3% of the total evapotranspiration. Direct root water uptake from the capillary fringe and groundwater, which is supplied by lateral groundwater flow, accounts for approximately 84% of the total transpiration. This study demonstrates the importance of implementing a dynamic root scheme in a land surface model for adequately simulating phreatophytic root water uptake and the associated latent heat flux.

The SMAP Level-4 ECO Project: Linking the Terrestrial Water and Carbon Cycles

NASA Technical Reports Server (NTRS)

Kolassa, J.; Reichle, R. H.; Liu, Qing; Koster, Randal D.

2017-01-01

The SMAP (Soil Moisture Active Passive) Level-4 projects aims to develop a fully coupled hydrology-vegetation data assimilation algorithm to generate improved estimates of modeled hydrological fields and carbon fluxes. This includes using the new NASA Catchment-CN (Catchment-Carbon-Nitrogen) model, which combines the Catchment land surface hydrology model with dynamic vegetation components from the Community Land Model version 4 (CLM4). As such, Catchment-CN allows a more realistic, fully coupled feedback between the land hydrology and the biosphere. The L4 ECO project further aims to inform the model through the assimilation of Soil Moisture Active Passive (SMAP) brightness temperature observations as well as observations of Moderate Resolution Imaging Spectroradiometer (MODIS) fraction of absorbed photosynthetically active radiation (FPAR). Preliminary results show that the assimilation of SMAP observations leads to consistent improvements in the model soil moisture skill. An evaluation of the Catchment-CN modeled vegetation characteristics showed that a calibration of the model's vegetation parameters is required before an assimilation of MODIS FPAR observations is feasible.

Using ground- and satellite-based measurements and models to quantify response to multiple disturbances and climate change in South African semi-arid ecosystems

NASA Astrophysics Data System (ADS)

Falge, Eva; Brümmer, Christian; Schmullius, Christiane; Scholes, Robert; Twine, Wayne; Mudau, Azwitamisi; Midgley, Guy; Hickler, Thomas; Bradshaw, Karen; Lück, Wolfgang; Thiel-Clemen, Thomas; du Toit, Justin; Sankaran, Vaith; Kutsch, Werner

2016-04-01

Sub-Saharan Africa currently experiences significant changes in shrubland, savanna and mixed woodland ecosystems driving degradation, affecting fire frequency and water availability, and eventually fueling climate change. The project 'Adaptive Resilience of Southern African Ecosystems' (ARS AfricaE) conducts research and develops scenarios of ecosystem development under climate change, for management support in conservation or for planning rural area development. For a network of research clusters along an aridity gradient in South Africa, we measure greenhouse gas exchange, ecosystem structure and eco-physiological properties as affected by land use change at paired sites with natural and altered vegetation. We set up dynamic vegetation models and individual-based models to predict ecosystem dynamics under (post) disturbance managements. We monitor vegetation amount and heterogeneity using remotely sensed images and aerial photography over several decades to examine time series of land cover change. Finally, we investigate livelihood strategies with focus on carbon balance components to develop sustainable management strategies for disturbed ecosystems and land use change. Emphasis is given on validation of estimates obtained from eddy covariance, model approaches and satellite derivations. We envision our methodological approach on a network of research clusters a valuable means to investigate potential linkages to concepts of adaptive resilience.

Modeling land use change impacts on water resources in a tropical West African catchment (Dano, Burkina Faso)

NASA Astrophysics Data System (ADS)

Yira, Y.; Diekkrüger, B.; Steup, G.; Bossa, A. Y.

2016-06-01

This study investigates the impacts of land use change on water resources in the Dano catchment, Burkina Faso, using a physically based hydrological simulation model and land use scenarios. Land use dynamic in the catchment was assessed through the analysis of four land use maps corresponding to the land use status in 1990, 2000, 2007, and 2013. A reclassification procedure levels out differences between the classification schemes of the four maps. The land use maps were used to build five land use scenarios corresponding to different levels of land use change in the catchment. Water balance was simulated by applying the Water flow and balance Simulation Model (WaSiM) using observed discharge, soil moisture, and groundwater level for model calibration and validation. Model statistical quality measures (R2, NSE and KGE) achieved during calibration and validation ranged between 0.6 and 0.9 for total discharge, soil moisture, and groundwater level, indicating a good agreement between observed and simulated variables. After a successful multivariate validation the model was applied to the land use scenarios. The land use assessment exhibited a decrease of savannah at an annual rate of 2% since 1990. Conversely, cropland and urban areas have increased. Since urban areas occupy only 3% of the catchment it can be assumed that savannah was mainly converted to cropland. The conversion rate of savannah was lower than the annual population growth of 3%. A clear increase in total discharge (+17%) and decrease in evapotranspiration (-5%) was observed following land use change in the catchment. A strong relationship was established between savannah degradation, cropland expansion, discharge increase and reduction of evapotranspiration. The increase in total discharge is related to high peak flow, suggesting (i) an increase in water resources that are not available for plant growth and human consumption and (ii) an alteration of flood risk for both the population within and downstream of the catchment.

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.

MSTV Mini-Symposium Preview

DTIC Science & Technology

2009-08-12

Man-In- The-Loop Simulation Integration & Demonstrators FTTS JLTV Future Force MRAP Thermal / CFD Crew Safety Structures/Durability Blast Dynamics ...Scott Stilson – General Dynamics Land Systems Chief Engineer, Stryker Modernization (S-Mod) Program The Application of Modeling and Simulation to the S...Military Ground Vehicles Nammalwar Purushothaman, Paramsothy Jayakumar & James Critchley – BAE Systems Sandip Datta & Venkat Pisipati – TAC World Wide

Fallow land effects on land-atmosphere interactions in California drought

NASA Astrophysics Data System (ADS)

Lu, Y.; Melton, F. S.; Kueppers, L. M.

2015-12-01

The recent drought in California increased the area of fallow land, which is cropland not planted or irrigated per normal agricultural practice. The effects of fallow land on land-atmosphere interactions in drought years are not well studied, but theoretically should alter local energy balance and surface climate relative to normal years, which in turn could affect neighboring cropland. We examined these effects using a regional climate model (Weather Research and Forecasting model) coupled with a dynamic crop growth model (Community Land Model) that has an irrigation scheme to study the effects of fallow land in 2014, an extreme drought year in California. In our study, we used satellite-derived maps of cultivated and fallowed acreage, and defined summer fallow land in 2014 as the reduced percentage of cultivated land for each grid cell relative to the 2011 cultivated area (2011 was the most recent year following a winter with average or above average precipitation). Using a sensitivity experiment that kept large-scale climate boundary conditions constant, we found that fallow land resulted in even dryer and warmer weather that worsened the drought impact. Fallow land increased 2-meter air temperature by 0.1- 4 °C with 0-80% fallow land, mainly due to an increase in nighttime temperature. Fallow land warmed the atmosphere up to 850hpa during the day, and after sunset, the warmed atmosphere emitted downward longwave radiation that prevented the surface from rapidly cooling, and therefore resulted in warmer nights. Fallow land reduced near surface relative humidity by 5-30% and increased vapor pressure deficit by 0.5-2 kPa. These drier conditions increased the irrigation water demand in the nearby cropland: crops required 1-25% more irrigation with 10-80% fallow land within the same 10km grid cell. Our study suggests that fallow land has large impacts on land-atmosphere interactions and increases irrigation requirements in nearby cropland.

Pathogen Transport and Fate Modeling in the Upper Salem River Watershed using SWAT Model

EPA Science Inventory

SWAT (Soil and Water Assessment Tool) is a dynamic watershed model that is applied to simulate the impact of land management practices on water quality over a continuous period. The Upper Salem River, located in Salem County New Jersey, is listed by the New Jersey Department of ...

Pathogen Transport and Fate Modeling in the Upper Salem River Watershed Using SWAT Model

EPA Science Inventory

SWAT (Soil and Water Assessment Tool) is a dynamic watershed model that is applied to simulate the impact of land management practices on water quality over a continuous period. The Upper Salem River, located in Salem County New Jersey, is listed by the New Jersey Department of ...

Integrating research on ecohydrology and land use change with land use management

NASA Astrophysics Data System (ADS)

Bass, Brad; Byers, Ralph E.; Lister, Nina-Marie

1998-10-01

One objective of the International Geosphere-Biosphere Programme is to provide a scientific basis for sustainable development policies. Land use change and ecohydrology are important components of this scientific basis, but predicting change is difficult because of the scale and complexity of the interactions between non-linear ecohydrological and socio-economic processes at different spatial and temporal scales. A systems framework, the Ecosystem Approach, has been developed to conceptualize these interactions for the purpose of providing information for sustainable development policy. The Ecosystem Approach combines the dynamics of the Holling figure-eight model - a conceptual model of dynamics that stresses discontinuous change and destruction as an internal property of the system - and the properties of self-organizing systems with the socio political aspects of decision making.The Ecosystem Approach highlights the problems of managing change in complex systems when that change may involve unpredictable shifts to a different attractor. Although there are methods available to detect the occurrence of such shifts, both detection and modelling are complicated by the presence of semi-stable attractors. When a model or an ecosystem is on a semi-stable attractor, it may appear to remain stable for an extended period prior to changing as a consequence of inherent instabilities. When the shift to a new attractor occurs, it is quite sudden and unpredictable. A technical discussion on prediction under conditions of semi-stability and chaos is included because it enhances our understanding of the role of surprise in ecosystems, as well as the utility of simulation models.The principles of the Ecosystem Approach are derived from the theoretical discussion and an example of a land use policy in the Huron Natural Area in south-western Ontario. These principles provide a clear role for scientific research, and particularly simulation modelling, within the larger context of policy and land use management.

Spatial and temporal diversification of crops dynamics in soil erosion modelling. A case study in the arable land of the upper Enziwigger River, Switzerland.

NASA Astrophysics Data System (ADS)

Borrelli, Pasquale; Meusburger, Katrin; Panagos, Panos; Ballabio, Cristiano; Alewell, Christine

2017-04-01

Accelerated soil erosion by water is a widespread phenomenon that affects several Mediterranean and Alpine landscapes causing on-site and off-site environmental impacts. Recognized in the EU Thematic Strategy for Soil Protection as one of the major threats to European soils (COM(2006)231), accelerated soil erosion is a major concern in landscape management and conservation planning (UN SDG 2.4). Agriculture and associated land-use change is the primary cause of accelerated soil erosion. This, because the soil displacement by water erosion mainly occurs when bare-sloped soil surfaces are exposed to the effect of rainfall and overland flow. The Revised Universal Soil Loss Equation (RUSLE) and other RUSLE-based models (which account for more than 90% of current worldwide modelling applications) describe the effect of the vegetation in the so called cover and management factor (C). The C-factor is generally the most challenging modelling component to compute over large study sites. To run a GIS-based RUSLE modelling for a study site greater than few hectares, the use of a simplified approach to assess the C-factor is inevitably necessary. In most of the cases, the C-factor values are assigned to the different land-use classes according to i) the C-values proposed in the literature, and ii) through land-use classifications based on vegetation indices (VI). In previous national (Land Use Policy, 50, 408-421, 2016) and pan-European (Environmental Science & Policy, 54, 438-447, 2015) studies, we computed regional C-values through weighted average operations combining crop statistics with remote sensing and GIS modelling techniques. Here, we present the preliminary results of an object-oriented change detection approach that we are testing to acquire spatial as well temporal crops dynamics at field-scale level in complex agricultural systems.

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

Luo, Yiqi; Shi, Zheng; Lu, Xingjie

Terrestrial ecosystems have absorbed roughly 30 % of anthropogenic CO 2 emissions over the past decades, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling and experimental and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under global change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C inputmore » (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, which is the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3-D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. In addition, the physical emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. Overall, this new mathematical framework offers new approaches to understanding, evaluating, diagnosing, and improving land C cycle models.« less

Modeling soil organic carbon stocks and changes in Spain using the GEFSOC system

NASA Astrophysics Data System (ADS)

Álvaro-Fuentes, Jorge; Easter, Mark; Cantero-Martínez, Carlos; Paustian, Keith

2010-05-01

Currently, there is little information about soil organic carbon (SOC) stocks in Spain. To date the effects of land-use and soil management on SOC stocks in Spain have been evaluated in experimental fields under certain soil and climate conditions. However, these field experiments do not account for the spatial variability in management, cropping systems and soil and climate characteristics that exist in the whole territory. More realistic approaches like ecosystem-level dynamic simulation systems linked to geographic information systems (GIS) allow better assessments of SOC stocks at a regional or national level. The Global Environmental Facility Soil Organic Carbon (GEFSOC) system was recently built for this purpose (Milne et al., 2007) and it incorporates three widely used models for estimating SOC dynamics: (a) the Century ecosystem model; (b) the RothC soil C decomposition model; and (c) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. We modeled 9.5 Mha in northeast Spain using the GEFSOC system to predict SOC stocks and changes comprising: pasture, forest, cereal-fallow, cereal monoculture, orchards, rice, irrigated land and grapes and olives. The spatial distribution of the different land use categories and their change over time was obtained from the European Corine database and from Spanish census data on land use from 1926 to 2007. At the same time, current and historical management information was collected from different sources in order to have a fairly well picture of changes in land use and management for this area. Soil parameters needed by the system were obtained from the European soil map (1 km x 1 km) and climate data was produced by the Meteorology State Agency (Ministry of the Environment and Rural and Marine Environs of Spain). The SOC stocks simulated were validated with SOC values from the European SOC map and from other national studies. Modeled SOC results suggested that spatial-based approaches are crucial for quantify SOC stocks and changes in Spain.

Experimental and analytical studies of advanced air cushion landing systems

NASA Technical Reports Server (NTRS)

Lee, E. G. S.; Boghani, A. B.; Captain, K. M.; Rutishauser, H. J.; Farley, H. L.; Fish, R. B.; Jeffcoat, R. L.

1981-01-01

Several concepts are developed for air cushion landing systems (ACLS) which have the potential for improving performance characteristics (roll stiffness, heave damping, and trunk flutter), and reducing fabrication cost and complexity. After an initial screening, the following five concepts were evaluated in detail: damped trunk, filled trunk, compartmented trunk, segmented trunk, and roll feedback control. The evaluation was based on tests performed on scale models. An ACLS dynamic simulation developed earlier is updated so that it can be used to predict the performance of full-scale ACLS incorporating these refinements. The simulation was validated through scale-model tests. A full-scale ACLS based on the segmented trunk concept was fabricated and installed on the NASA ACLS test vehicle, where it is used to support advanced system development. A geometrically-scaled model (one third full scale) of the NASA test vehicle was fabricated and tested. This model, evaluated by means of a series of static and dynamic tests, is used to investigate scaling relationships between reduced and full-scale models. The analytical model developed earlier is applied to simulate both the one third scale and the full scale response.

Dust Storm Monitoring Using Satellite Observatory and Numerical Modeling Analysis

NASA Astrophysics Data System (ADS)

Taghavi, Farahnaz

In recent years, the frequency of dust pollution events in the Iran Southwest are increased which caused huge damage and imposed a negative impacts on air quality, airport traffic and people daily life in local areas. Dust storms in this area usually start with the formation of a low-pressure center over the Arabian Peninsula. The main objectives of this study is to asses and monitor the movement of aerosols and pollutions from origin source to local areas using satellite imagery and numerical modeling analysis. Observational analyses from NCEP such as synoptic data (Uwind,Vwind,Vorticity and Divergence Fields), upper air radiosonde, measured visibility distributions, land cover data are also used in model comparisons to show differences in occurrence of dust events. The evolution and dynamics of this phenomena are studied on the based a method to modify the initial state of NWP output using discrepancies between dynamic fields and WV imagery in a grid. Results show that satellite images offers a means to control the behavior of numeric models and also the model using land cover data improving the wind-blown dust modeling.

Shifts in wind energy potential following land-use driven vegetation dynamics in complex terrain.

PubMed

Fang, Jiannong; Peringer, Alexander; Stupariu, Mihai-Sorin; Pǎtru-Stupariu, Ileana; Buttler, Alexandre; Golay, Francois; Porté-Agel, Fernando

2018-10-15

Many mountainous regions with high wind energy potential are characterized by multi-scale variabilities of vegetation in both spatial and time dimensions, which strongly affect the spatial distribution of wind resource and its time evolution. To this end, we developed a coupled interdisciplinary modeling framework capable of assessing the shifts in wind energy potential following land-use driven vegetation dynamics in complex mountain terrain. It was applied to a case study area in the Romanian Carpathians. The results show that the overall shifts in wind energy potential following the changes of vegetation pattern due to different land-use policies can be dramatic. This suggests that the planning of wind energy project should be integrated with the land-use planning at a specific site to ensure that the expected energy production of the planned wind farm can be reached over its entire lifetime. Moreover, the changes in the spatial distribution of wind and turbulence under different scenarios of land-use are complex, and they must be taken into account in the micro-siting of wind turbines to maximize wind energy production and minimize fatigue loads (and associated maintenance costs). The proposed new modeling framework offers, for the first time, a powerful tool for assessing long-term variability in local wind energy potential that emerges from land-use change driven vegetation dynamics over complex terrain. Following a previously unexplored pathway of cause-effect relationships, it demonstrates a new linkage of agro- and forest policies in landscape development with an ultimate trade-off between renewable energy production and biodiversity targets. Moreover, it can be extended to study the potential effects of micro-climatic changes associated with wind farms on vegetation development (growth and patterning), which could in turn have a long-term feedback effect on wind resource distribution in mountainous regions. Copyright © 2018 Elsevier B.V. All rights reserved.

Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models

NASA Astrophysics Data System (ADS)

Chaney, N.; Shevliakova, E.; Malyshev, S.; Van Huijgevoort, M.; Milly, C.; Sulman, B. N.

2016-12-01

Terrestrial land surface processes play a critical role in the Earth system; they have a profound impact on the global climate, food and energy production, freshwater resources, and biodiversity. One of the most fascinating yet challenging aspects of characterizing terrestrial ecosystems is their field-scale (˜30 m) spatial heterogeneity. It has been observed repeatedly that the water, energy, and biogeochemical cycles at multiple temporal and spatial scales have deep ties to an ecosystem's spatial structure. Current Earth system models largely disregard this important relationship leading to an inadequate representation of ecosystem dynamics. In this presentation, we will show how existing global environmental datasets can be harnessed to explicitly represent field-scale spatial heterogeneity in Earth system models. For each macroscale grid cell, these environmental data are clustered according to their field-scale soil and topographic attributes to define unique sub-grid tiles. The state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) land model is then used to simulate these tiles and their spatial interactions via the exchange of water, energy, and nutrients along explicit topographic gradients. Using historical simulations over the contiguous United States, we will show how a robust representation of field-scale spatial heterogeneity impacts modeled ecosystem dynamics including the water, energy, and biogeochemical cycles as well as vegetation composition and distribution.

Variable strategy model of the human operator

NASA Astrophysics Data System (ADS)

Phillips, John Michael

Human operators often employ discontinuous or "bang-bang" control strategies when performing large-amplitude acquisition tasks. The current study applies Variable Structure Control (VSC) techniques to model human operator behavior during acquisition tasks. The result is a coupled, multi-input model replicating the discontinuous control strategy. In the VSC formulation, a switching surface is the mathematical representation of the operator's control strategy. The performance of the Variable Strategy Model (VSM) is evaluated by considering several examples, including the longitudinal control of an aircraft during the visual landing task. The aircraft landing task becomes an acquisition maneuver whenever large initial offsets occur. Several different strategies are explored in the VSM formulation for the aircraft landing task. First, a switching surface is constructed from literal interpretations of pilot training literature. This approach yields a mathematical representation of how a pilot is trained to fly a generic aircraft. This switching surface is shown to bound the trajectory response of a group of pilots performing an offset landing task in an aircraft simulator study. Next, front-side and back-side landing strategies are compared. A back-side landing strategy is found to be capable of landing an aircraft flying on either the front side or back side of the power curve. However, the front-side landing strategy is found to be insufficient for landing an aircraft flying on the back side. Finally, a more refined landing strategy is developed that takes into the account the specific aircraft's dynamic characteristics. The refined strategy is translated back into terminology similar to the existing pilot training literature.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Empirical relationships between soil moisture, albedo, and the planetary boundary layer height: a two-layer bucket model approach

NASA Astrophysics Data System (ADS)

Sanchez-Mejia, Z. M.; Papuga, S. A.

2013-12-01

In semiarid regions, where water resources are limited and precipitation dynamics are changing, understanding land surface-atmosphere interactions that regulate the coupled soil moisture-precipitation system is key for resource management and planning. We present a modeling approach to study soil moisture and albedo controls on planetary boundary layer height (PBLh). We used data from the Santa Rita Creosote Ameriflux site and Tucson Airport atmospheric sounding to generate empirical relationships between soil moisture, albedo and PBLh. We developed empirical relationships and show that at least 50% of the variation in PBLh can be explained by soil moisture and albedo. Then, we used a stochastically driven two-layer bucket model of soil moisture dynamics and our empirical relationships to model PBLh. We explored soil moisture dynamics under three different mean annual precipitation regimes: current, increase, and decrease, to evaluate at the influence on soil moisture on land surface-atmospheric processes. While our precipitation regimes are simple, they represent future precipitation regimes that can influence the two soil layers in our conceptual framework. For instance, an increase in annual precipitation, could impact on deep soil moisture and atmospheric processes if precipitation events remain intense. We observed that the response of soil moisture, albedo, and the PBLh will depend not only on changes in annual precipitation, but also on the frequency and intensity of this change. We argue that because albedo and soil moisture data are readily available at multiple temporal and spatial scales, developing empirical relationships that can be used in land surface - atmosphere applications are of great value.

Unravelling the Impacts of Climate and People on Vegetation Dynamics in the Sahel 1982- 2002

NASA Astrophysics Data System (ADS)

Seaquist, J. W.; Hickler, T.; Eklundh, L.; Ardö, J.; Heumann, B. W.

2009-05-01

Satellite sensors have recently shown that much of the Sahel belt of north Africa has experienced significant increases in photosynthetic activity since the early 1980s. This has reignited old debates about the role that people play in shaping land surface status at broad geographical extents. If the human 'footprint' on Sahel vegetation dynamics is measurable, then such impacts may be significant enough alter broad-scale both carbon budgets and climate via land surface atmosphere feedbacks. We test the hypothesis that people have had a measurable impact on vegetation dynamics in the Sahel for the period 1982-2002. We accomplish this by mapping the agreement between potential natural vegetation dynamics predicted by a process-based ecosystem model (Lund Potsdam Jena-Dynamic Global Vegetation Model) and satellite-derived greenness observations (Global Inventory Modelling and Mapping Studies data set) across a geographic grid at a spatial resolution of 0.5 degrees. We then relate this agreement metric to state-of-the-art data sets on demographics, pasture, and cropping. Demographic and agricultural pressures in the Sahel are unable to account for differences between simulated and observed vegetation dynamics, even for the most densely populated areas. But we do identify a weak, positive correlation between data-model agreement and pasture intensity at the Sahel-wide level. This indicates that herding or grazing does not appreciably affect vegetation dynamics in the region. Either people have not had a significant impact on vegetation dynamics in the Sahel or the identification of a human 'footprint' is precluded by inconsistent or subtle vegetation response to complex socio-environmental interactions, and/or limitations in the data used for this study. This research showcases untapped potential for combining ecosystem process models with remote sensing at broad spatial extents for examining the underlying causes of ecosystem change.

Modelling and analyzing the watershed dynamics using Cellular Automata (CA)-Markov model - A geo-information based approach

NASA Astrophysics Data System (ADS)

Behera, Mukunda D.; Borate, Santosh N.; Panda, Sudhindra N.; Behera, Priti R.; Roy, Partha S.

2012-08-01

Improper practices of land use and land cover (LULC) including deforestation, expansion of agriculture and infrastructure development are deteriorating watershed conditions. Here, we have utilized remote sensing and GIS tools to study LULC dynamics using Cellular Automata (CA)-Markov model and predicted the future LULC scenario, in terms of magnitude and direction, based on past trend in a hydrological unit, Choudwar watershed, India. By analyzing the LULC pattern during 1972, 1990, 1999 and 2005 using satellite-derived maps, we observed that the biophysical and socio-economic drivers including residential/industrial development, road-rail and settlement proximity have influenced the spatial pattern of the watershed LULC, leading to an accretive linear growth of agricultural and settlement areas. The annual rate of increase from 1972 to 2004 in agriculture land, settlement was observed to be 181.96, 9.89 ha/year, respectively, while decrease in forest, wetland and marshy land were 91.22, 27.56 and 39.52 ha/year, respectively. Transition probability and transition area matrix derived using inputs of (i) residential/industrial development and (ii) proximity to transportation network as the major causes. The predicted LULC scenario for the year 2014, with reasonably good accuracy would provide useful inputs to the LULC planners for effective management of the watershed. The study is a maiden attempt that revealed agricultural expansion is the main driving force for loss of forest, wetland and marshy land in the Choudwar watershed and has the potential to continue in future. The forest in lower slopes has been converted to agricultural land and may soon take a call on forests occurring on higher slopes. Our study utilizes three time period changes to better account for the trend and the modelling exercise; thereby advocates for better agricultural practices with additional energy subsidy to arrest further forest loss and LULC alternations.

[Simulation for balanced effect of soil and water resources on cultivated land in Naoli River Basin, Northeast China under the RCPs climate scene].

PubMed

Zhou, Hao; Lei, Guo Ping; Yang, Xue Xin; Zhao, Yu Hui; Zhang, Ji Xin

2018-04-01

Under the scenarios of climate change, balancing the land and water resources is one of the key problems needed to be solved in land development. To reveal the water dynamics of the cultivated land in Naoli River Basin, we simulated the future scenarios by using the future land use simulation model based on Landsat Satellite images, the DEM data and the meteorological data. Results showed that the growth rate of cultivated land gradually decreased. It showed different changing characteristics in different time periods, which led to different balancing effect between land and water resources. In 1990, the water dynamics of the cultivated land resources was in good state, At the same time, the adjustment of crops structure caused the paddy fields increased dramatically. During 2002 to 2014, the cultivated land that in moderate and serious moisture shortage state increased slightly, the water deficit was deteriorating to a certain degree, and maintained sound development of water profit and loss situation gradually. By comparing the simulation accuracy with different spatial resolutions and time scales, we selected 200 m as the spatial resolution of the simulation, and simulated the land use status in 2038. The simulation results showed that the cultivated land's water profit and loss degree in the river basin showed significant polarization characteristic, in that the water profit and loss degree of the cultivated land would be further intensified, the area with the higher grades of moisture profit and loss degree would distribute more centralized, and partially high evaluated grades for the moisture shortage would expand. It is needed to develop the cultivated land irrigation schemes and adjust the cultivated land in Naoli River Basin to balance soil and water resources.

Modeling Vegetation Growth Impact on Groundwater Recharge

NASA Astrophysics Data System (ADS)

Anurag, H.; Ng, G. H. C.; Tipping, R.

2017-12-01

Vegetation growth is affected by variability in climate and land-cover / land-use over a range of temporal and spatial scales. Vegetation also modifies water budget through interception and evapotranspiration and thus has a significant impact on groundwater recharge. Most groundwater recharge assessments represent vegetation using specified, static parameter, such as for leaf-area-index, but this neglects the effect of vegetation dynamics on recharge estimates. Our study addresses this gap by including vegetation growth in model simulations of recharge. We use NCAR's Community Land Model v4.5 with its BGC module (BGC is the new CLM4.5 biogeochemistry). It integrates prognostic vegetation growth with land-surface and subsurface hydrological processes and can thus capture the effect of vegetation on groundwater. A challenge, however, is the need to resolve uncertainties in model inputs ranging from vegetation growth parameters all the way down to the water table. We have compiled diverse data spanning meteorological inputs to subsurface geology and use these to implement ensemble model simulations to evaluate the possible effects of dynamic vegetation growth (versus specified, static vegetation parameterizations) on estimating groundwater recharge. We present preliminary results for select data-intensive test locations throughout the state of Minnesota (USA), which has a sharp east-west precipitation gradient that makes it an apt testbed for examining ecohydrologic relationships across different temperate climatic settings and ecosystems. Using the ensemble simulations, we examine the effect of seasonal to interannual variability of vegetation growth on recharge and water table depths, which has implications for predicting the combined impact of climate, vegetation, and geology on groundwater resources. Future work will include distributed model simulations over the entire state, as well as conditioning uncertain vegetation and subsurface parameters on remote sensing data and statewide water table records using data assimilation.

Towards integrated modelling of soil organic carbon cycling at landscape scale

NASA Astrophysics Data System (ADS)

Viaud, V.

2009-04-01

Soil organic carbon (SOC) is recognized as a key factor of the chemical, biological and physical quality of soil. Numerous models of soil organic matter turnover have been developed since the 1930ies, most of them dedicated to plot scale applications. More recently, they have been applied to national scales to establish the inventories of carbon stocks directed by the Kyoto protocol. However, only few studies consider the intermediate landscape scale, where the spatio-temporal pattern of land management practices, its interactions with the physical environment and its impacts on SOC dynamics can be investigated to provide guidelines for sustainable management of soils in agricultural areas. Modelling SOC cycling at this scale requires accessing accurate spatially explicit input data on soils (SOC content, bulk density, depth, texture) and land use (land cover, farm practices), and combining both data in a relevant integrated landscape representation. The purpose of this paper is to present a first approach to modelling SOC evolution in a small catchment. The impact of the way landscape is represented on SOC stocks in the catchment was more specifically addressed. This study was based on the field map, the soil survey, the crop rotations and land management practices of an actual 10-km² agricultural catchment located in Brittany (France). RothC model was used to drive soil organic matter dynamics. Landscape representation in the form of a systematic regular grid, where driving properties vary continuously in space, was compared to a representation where landscape is subdivided into a set of homogeneous geographical units. This preliminary work enabled to identify future needs to improve integrated soil-landscape modelling in agricultural areas.

Integrating Ecosystem Carbon Dynamics into State-and-Transition Simulation Models of Land Use/Land Cover Change

NASA Astrophysics Data System (ADS)

Sleeter, B. M.; Daniel, C.; Frid, L.; Fortin, M. J.

2016-12-01

State-and-transition simulation models (STSMs) provide a general approach for incorporating uncertainty into forecasts of landscape change. Using a Monte Carlo approach, STSMs generate spatially-explicit projections of the state of a landscape based upon probabilistic transitions defined between states. While STSMs are based on the basic principles of Markov chains, they have additional properties that make them applicable to a wide range of questions and types of landscapes. A current limitation of STSMs is that they are only able to track the fate of discrete state variables, such as land use/land cover (LULC) classes. There are some landscape modelling questions, however, for which continuous state variables - for example carbon biomass - are also required. Here we present a new approach for integrating continuous state variables into spatially-explicit STSMs. Specifically we allow any number of continuous state variables to be defined for each spatial cell in our simulations; the value of each continuous variable is then simulated forward in discrete time as a stochastic process based upon defined rates of change between variables. These rates can be defined as a function of the realized states and transitions of each cell in the STSM, thus providing a connection between the continuous variables and the dynamics of the landscape. We demonstrate this new approach by (1) developing a simple IPCC Tier 3 compliant model of ecosystem carbon biomass, where the continuous state variables are defined as terrestrial carbon biomass pools and the rates of change as carbon fluxes between pools, and (2) integrating this carbon model with an existing LULC change model for the state of Hawaii, USA.

[Temporal-spatial characteristics of land use in Xinjian County, Jiangxi Province].

PubMed

Chen, Wenbo; Zhao, Xiaofan; Cui, Lijuan

2006-05-01

With the support of RS and GIS, and using a series of indices in characterizing the dynamics of land use, this paper studied the temporal-spatial characteristics of land use in Xinjian County, Jiangxi Province, between 1991 and 2000. The results indicated that among single land use types, the area for construction changed mostly. The annual change speed of comprehensive land dynamic index between 1991 and 1995 was 0.5 times higher than that between 1996 and 2000, and the utilization grade in 1991, 1996 and 2000 was 243.7, 44.1 and 244.9, respectively, being a little higher than the national average grade. The land inflow and outflow in 1996 to approximately 2000 was lower than that in 1991 to approximately 1995, and the land use change was from bilateral dynamics to unilateral unbalanced dynamics.

Simulating the Conversion of Rural Settlements to Town Land Based on Multi-Agent Systems and Cellular Automata

PubMed Central

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans. PMID:24244472

Choosing the target of adaptive soil erosion management in Mediterranean. Long vs. Extreme erosion, internal vs. external catchment dynamics

NASA Astrophysics Data System (ADS)

Smetanova, Anna; Follain, Stéphane; David, Mélodie; Ciampalini, Rossano; Raclot, Damien; Crabit, Armand; Le Bissonnais, Yves

2017-04-01

For soil resources protection and regulation of soil erosion off-site effects in Mediterranean, it is inevitable to adjust current land management planning to both, event magnitude and long-term erosion means [2, 3, 5]. Science-based soil protection measures need to be adjusted to spatial and temporal scale of practice differing between stakeholders and management aims, and reflect increasing frequency of torrential rainfalls leading to very high erosion rates in short time [3, 4]. In order to address selection of zero-soil erosion land management target, this study applies modelling approach for comparison of 7 land use scenarios using the LandSoil model [1]. We propose comparison of internal vs. external catchment dynamic at extreme event- and long-term scale as a tool for understanding effect of land management in targeting emerging erosion and connectivity patterns. Our results suggest, that proposed approach can be applied to identify best management scenario practices regarding different management aims of farmers and watershed managers. [1] Ciampalini R, Follain S, Le Bissonnais Y. 2012. LandSoil: A model for analysing the impact of erosion on agricultural landscape evolution. Geomorphology 175-176: 25-37. [2] David M, Follain S, Ciampalini R, Le Bissonnais Y, Couturier A, Walter C. 2014. Simulation of medium-term soil redistributions for different land use and landscape design scenarios within a vineyard landscape in Mediterranean France. Geomorphology 214: 10-21. [3] Smetanová A, Le Bissonnais Y, Raclot D, Nunes JP, Licciardello F, Le Bouteiller C, Latron J, Rodríguez-Caballero E, Mathys N, Klotz S, Mekki I, Gallart F, Solé Benet A, Pérez Gallego N, Andrieux P, Moussa R, Planchon O, Marisa Santos J, Alshihabi O, Chikhaoui M., submitted. Patterns of temporal variability and time compression of sediment yield in small Mediterranean catchments. Soil Use & Management [4] Smetanová A, Paton E, Maynard C, Tindale S, Fernandez-Getino A-P, Marques MJ, Bracken L, Le Bissonnais Y, Keesstra S. submitted -b. Stakeholders' perception of the relevance of water and sediment connectivity in water and land management. Land Degradation & Development [5] Stroosnijder L. 2005. Measurement of erosion: Is it possible? CATENA 64: 162-173.

Simulating the biogeochemical and biogeophysical impacts of transient land cover change and wood harvest in the Community Climate System Model (CCSM4) from 1850 to 2100

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

Lawrence, Peter J.; Feddema, Johannes J.; Bonan, Gordon B.

To assess the climate impacts of historical and projected land cover change and land use in the Community Climate System Model (CCSM4) we have developed new time series of transient Community Land Model (CLM4) Plant Functional Type (PFT) parameters and wood harvest parameters. The new parameters capture the dynamics of the Coupled Model Inter-comparison Project phase 5 (CMIP5) land cover change and wood harvest trajectories for the historical period from 1850 to 2005, and for the four Representative Concentration Pathways (RCP) periods from 2006 to 2100. Analysis of the biogeochemical impacts of land cover change in CCSM4 with the parametersmore » found the model produced an historical cumulative land use flux of 148.4 PgC from 1850 to 2005, which was in good agreement with other global estimates of around 156 PgC for the same period. The biogeophysical impacts of only applying the transient land cover change parameters in CCSM4 were cooling of the near surface atmospheric over land by -0.1OC, through increased surface albedo and reduced shortwave radiation absorption. When combined with other transient climate forcings, the higher albedo from land cover change was overwhelmed at global scales by decreases in snow albedo from black carbon deposition and from high latitude warming. At regional scales however the land cover change forcing persisted resulting in reduced warming, with the biggest impacts in eastern North America. The future CCSM4 RCP simulations showed that the CLM4 transient PFT and wood harvest parameters could be used to represent a wide range of human land cover change and land use scenarios. Furthermore, these simulations ranged from the RCP 4.5 reforestation scenario that was able to draw down 82.6 PgC from the atmosphere, to the RCP 8.5 wide scale deforestation scenario that released 171.6 PgC to the atmosphere.« less

Proceedings of the Workshop on Transportation/Urban Form Interactions held at Cambridge, MA. on August 14-15, 1978

DOT National Transportation Integrated Search

1979-06-01

Contents: A form of utility function for the UMOT model; An analysis of transportation/land use interactions; Toward a methodology to shape urban structure; Approaches for improving urban travel forecasts; Quasi-dynamic urban location models with end...

Microsimulation of household and firm behaviors : coupled models of land use and travel demand in Austin, Texas

DOT National Transportation Integrated Search

2007-12-01

Households and firms are key drivers of urban growth, yet models for forecasting travel demand often : ignore their dynamic evolution and several key decision processes. An understanding of household and : firm behavior over time is critical in antic...

Comparison of algorithms and parameterisations for infiltration into organic-covered permafrost soils

USDA-ARS?s Scientific Manuscript database

Infiltration into frozen and unfrozen soils is critical in hydrology, controlling active layer soil water dynamics and influencing runoff. Few Land Surface Models (LSMs) and Hydrological Models (HMs) have been developed, adapted or tested for frozen conditions and permafrost soils. Considering the v...

Study of the Effect of Wind Speed on Evaporation from Soil Through Integrated Modeling of Atmospheric Boundary Layer and Shallow Subsurface

NASA Astrophysics Data System (ADS)

Smits, K. M.; Davarzani, H.; Illangasekare, T. H.

2012-12-01

The study of the interaction between the land and atmosphere is paramount to our understanding of many emerging problems to include climate change and the movement of green house gases such as possible leaking of sequestered CO2. Soil moisture distribution in the shallow subsurface becomes a critical factor in these problems. The heat and mass flux in the form of soil evaporation across the land surface couples the atmospheric boundary layer to the shallow subsurface. The coupling between land and the atmosphere leads to highly dynamic interactions between the porous media properties, transport processes and boundary conditions, resulting in dynamic evaporative behavior. However, the coupling at the land-atmospheric interface is rarely considered in most current models and their validation for practical applications. This is due to the complexity of the problem in field scenarios and the scarcity of field or laboratory data capable of testing and refining coupled energy and mass transfer theories. In most efforts to compute evaporation from soil, only indirect coupling is provided to characterize the interaction between non-isothermal multiphase flows under realistic atmospheric conditions even though heat and mass flux are controlled by the coupled dynamics of the land and the atmospheric boundary layer. In earlier drying modeling concepts, imposing evaporation flux (kinetic of relative humidity) and temperature as surface boundary condition is often needed. With the goal of improving our understanding of the land/atmospheric coupling, we developed a model based on the coupling of Navier-Stokes free flow and Darcy flow in porous medium. The model consists of the coupled equations of mass conservation for the liquid phase (water) and gas phase (water vapor and air) in porous medium with gas phase (water vapor and air) in free flow domain under non-isothermal, non-equilibrium conditions. The boundary conditions at the porous medium-free flow medium interface include dynamical, thermal and solutal equilibriums, and using the Beavers-Joseph slip boundary condition. What is unique about this model is that the evaporation rate and soil surface temperature conditions come directly from the model output. In order to experimentally validate the numerical results, we developed and used a unique two dimensional wind tunnel placed above a soil tank equipped with a network of different sensors. A series of experiments under varying boundary conditions were performed. Precision data under well-controlled transient heat and wind boundary conditions was generated. Results from numerical simulations were compared with experimental data. Results demonstrate that the coupling concept can predict the different stages of the drying process in porous media with good accuracy. Increasing the wind speed increases the first stage evaporation rate and decreases the transition time at low velocity values; then, at high values of wind speed the evaporation rate becomes less dependent of flow in free fluid. In the opposite, the impact of the wind speed on the second stage evaporation (diffusion dominant stage) is not significant. The proposed theoretical model can be used to predict the evaporation process where a porous medium flow is coupled to a free flow for different practical applications.

Comparing Noah-MP simulations of energy and water fluxes in the soil-vegetation-atmosphere continuum with plot scale measurements

NASA Astrophysics Data System (ADS)

Gayler, Sebastian; Wöhling, Thomas; Högy, Petra; Ingwersen, Joachim; Wizemann, Hans-Dieter; Wulfmeyer, Volker; Streck, Thilo

2013-04-01

During the last years, land-surface models have proven to perform well in several studies that compared simulated fluxes of water and energy from the land surface to the atmosphere against measured fluxes at the plot-scale. In contrast, considerable deficits of land-surface models have been identified to simulate soil water fluxes and vertical soil moisture distribution. For example, Gayler et al. (2013) showed that simplifications in the representation of root water uptake can result in insufficient simulations of the vertical distribution of soil moisture and its dynamics. However, in coupled simulations of the terrestrial water cycle, both sub-systems, the atmosphere and the subsurface hydrogeo-system, must fit together and models are needed, which are able to adequately simulate soil moisture, latent heat flux, and their interrelationship. Consequently, land-surface models must be further improved, e.g. by incorporation of advanced biogeophysics models. To improve the conceptual realism in biophysical and hydrological processes in the community land surface model Noah, this model was recently enhanced to Noah-MP by a multi-options framework to parameterize individual processes (Niu et al., 2011). Thus, in Noah-MP the user can choose from several alternative models for vegetation and hydrology processes that can be applied in different combinations. In this study, we evaluate the performance of different Noah-MP model settings to simulate water and energy fluxes across the land surface at two contrasting field sites in South-West Germany. The evaluation is done in 1D offline-mode, i.e. without coupling to an atmospheric model. The atmospheric forcing is provided by measured time series of the relevant variables. Simulation results are compared with eddy covariance measurements of turbulent fluxes and measured time series of soil moisture at different depths. The aims of the study are i) to carve out the most appropriate combination of process parameterizations in Noah-MP to simultaneously match the different components of the water and energy cycle at the field sites under consideration, and ii) to estimate the uncertainty in model structure. We further investigate the potential to improve simulation results by incorporating concepts of more advanced root water uptake models from agricultural field scale models into the land-surface-scheme. Gayler S, Ingwersen J, Priesack E, Wöhling T, Wulfmeyer V, Streck T (2013): Assessing the relevance of sub surface processes for the simulation of evapotranspiration and soil moisture dynamics with CLM3.5: Comparison with field data and crop model simulations. Environ. Earth Sci., 69(2), under revision. Niu G-Y, Yang Z-L, Mitchell KE, Chen F, Ek MB, Barlage M, Kumar A, Manning K, Niyogi D, Rosero E, Tewari M and Xia Y (2011): The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. Journal of Geophysical Research 116(D12109).

Multi-criteria Evaluation of Discharge Simulation in Dynamic Global Vegetation Models

NASA Astrophysics Data System (ADS)

Yang, H.; Piao, S.; Zeng, Z.; Ciais, P.; Yin, Y.; Friedlingstein, P.; Sitch, S.; Ahlström, A.; Guimberteau, M.; Huntingford, C.; Levis, S.; Levy, P. E.; Huang, M.; Li, Y.; Li, X.; Lomas, M.; Peylin, P. P.; Poulter, B.; Viovy, N.; Zaehle, S.; Zeng, N.; Zhao, F.; Wang, L.

2015-12-01

In this study, we assessed the performance of discharge simulations by coupling the runoff from seven Dynamic Global Vegetation Models (DGVMs; LPJ, ORCHIDEE, Sheffield-DGVM, TRIFFID, LPJ-GUESS, CLM4CN, and OCN) to one river routing model for 16 large river basins. The results show that the seasonal cycle of river discharge is generally modelled well in the low and mid latitudes, but not in the high latitudes, where the peak discharge (due to snow and ice melting) is underestimated. For the annual mean discharge, the DGVMs chained with the routing model show an underestimation. Furthermore the 30-year trend of discharge is also under-estimated. For the inter-annual variability of discharge, a skill score based on overlapping of probability density functions (PDFs) suggests that most models correctly reproduce the observed variability (correlation coefficient higher than 0.5; i.e. models account for 50% of observed inter-annual variability) except for the Lena, Yenisei, Yukon, and the Congo river basins. In addition, we compared the simulated runoff from different simulations where models were forced with either fixed or varying land use. This suggests that both seasonal and annual mean runoff has been little affected by land use change, but that the trend itself of runoff is sensitive to land use change. None of the models when considered individually show significantly better performances than any other and in all basins. This suggests that based on current modelling capability, a regional-weighted average of multi-model ensemble projections might be appropriate to reduce the bias in future projection of global river discharge.

A stand-alone tree demography and landscape structure module for Earth system models: integration with inventory data from temperate and boreal forests

NASA Astrophysics Data System (ADS)

Haverd, V.; Smith, B.; Nieradzik, L. P.; Briggs, P. R.

2014-08-01

Poorly constrained rates of biomass turnover are a key limitation of Earth system models (ESMs). In light of this, we recently proposed a new approach encoded in a model called Populations-Order-Physiology (POP), for the simulation of woody ecosystem stand dynamics, demography and disturbance-mediated heterogeneity. POP is suitable for continental to global applications and designed for coupling to the terrestrial ecosystem component of any ESM. POP bridges the gap between first-generation dynamic vegetation models (DVMs) with simple large-area parameterisations of woody biomass (typically used in current ESMs) and complex second-generation DVMs that explicitly simulate demographic processes and landscape heterogeneity of forests. The key simplification in the POP approach, compared with second-generation DVMs, is to compute physiological processes such as assimilation at grid-scale (with CABLE (Community Atmosphere Biosphere Land Exchange) or a similar land surface model), but to partition the grid-scale biomass increment among age classes defined at sub-grid-scale, each subject to its own dynamics. POP was successfully demonstrated along a savanna transect in northern Australia, replicating the effects of strong rainfall and fire disturbance gradients on observed stand productivity and structure. Here, we extend the application of POP to wide-ranging temporal and boreal forests, employing paired observations of stem biomass and density from forest inventory data to calibrate model parameters governing stand demography and biomass evolution. The calibrated POP model is then coupled to the CABLE land surface model, and the combined model (CABLE-POP) is evaluated against leaf-stem allometry observations from forest stands ranging in age from 3 to 200 year. Results indicate that simulated biomass pools conform well with observed allometry. We conclude that POP represents an ecologically plausible and efficient alternative to large-area parameterisations of woody biomass turnover, typically used in current ESMs.

The Net Carbon Flux due to Deforestation and Forest Re-Growth in the Brazilian Amazon: Analysis using a Process-Based Model

NASA Technical Reports Server (NTRS)

Hirsch, A. I.; Little, W. S.; Houghton, R. A.; Scott, N. A.; White, J. D.

2004-01-01

We developed a process-based model of forest growth, carbon cycling, and land cover dynamics named CARLUC (for CARbon and Land Use Change) to estimate the size of terrestrial carbon pools in terra firme (non-flooded) forests across the Brazilian Legal Amazon and the net flux of carbon resulting from forest disturbance and forest recovery from disturbance. Our goal in building the model was to construct a relatively simple ecosystem model that would respond to soil and climatic heterogeneity that allows us to study of the impact of Amazonian deforestation, selective logging, and accidental fire on the global carbon cycle. This paper focuses on the net flux caused by deforestation and forest re-growth over the period from 1970-1998. We calculate that the net flux to the atmosphere during this period reached a maximum of approx. 0.35 PgC/yr (1PgC = 1 x 10(exp I5) gC) in 1990, with a cumulative release of approx. 7 PgC from 1970- 1998. The net flux is higher than predicted by an earlier study by a total of 1 PgC over the period 1989-1 998 mainly because CARLUC predicts relatively high mature forest carbon storage compared to the datasets used in the earlier study. Incorporating the dynamics of litter and soil carbon pools into the model increases the cumulative net flux by approx. 1 PgC from 1970-1998, while different assumptions about land cover dynamics only caused small changes. The uncertainty of the net flux, calculated with a Monte-Carlo approach, is roughly 35% of the mean value (1 SD).

How does soil erosion influence the terrestrial carbon cycle and the impacts of land use and land cover change?

NASA Astrophysics Data System (ADS)

Naipal, V.; Wang, Y.; Ciais, P.; Guenet, B.; Lauerwald, R.

2017-12-01

The onset of agriculture has accelerated soil erosion rates significantly, mobilizing vast quantities of soil organic carbon (SOC) globally. Studies show that at timescales of decennia to millennia this mobilized SOC can significantly alter previously estimated carbon emissions from land use and land cover change (LULCC). However, a full understanding of the impact of soil erosion on land-atmosphere carbon exchange is still missing. The aim of our study is to better constrain the terrestrial carbon fluxes by developing methods, which are compatible with earth system models (ESMs), and explicitly represent the links between soil erosion and carbon dynamics. For this we use an emulator that represents the carbon cycle of ORCHIDEE, which is the land component of the IPSL ESM, in combination with an adjusted version of the Revised Universal Soil Loss Equation (RUSLE) model. We applied this modeling framework at the global scale to evaluate how soil erosion influenced the terrestrial carbon cycle in the presence of elevated CO2, regional climate change and land use change. Here, we focus on the effects of soil detachment by erosion only and do not consider sediment transport and deposition. We found that including soil erosion in the SOC dynamics-scheme resulted in two times more SOC being lost during the historical period (1850-2005 AD). LULCC is the main contributor to this SOC loss, whose impact on the SOC stocks is significantly amplified by erosion. Regionally, the influence of soil erosion varies significantly, depending on the magnitude of the perturbations to the carbon cycle and the effects of LULCC and climate change on soil erosion rates. We conclude that it is necessary to include soil erosion in assessments of LULCC, and to explicitly consider the effects of elevated CO2 and climate change on the carbon cycle and on soil erosion, for better quantification of past, present, and future LULCC carbon emissions.

Regional Climate Simulations of the Hydrological Cycle in the Iberian Peninsula with a Coupled WRF-HYDRO Model

NASA Astrophysics Data System (ADS)

Rios-Entenza, A.; Miguez-Macho, G.

2008-12-01

Land-atmosphere water exchanges and heat fluxes play an important role in climate and particularly in controlling precipitation in water-limited regions. One of such regions is the Iberian Peninsula, and in this study we examine the relevance of water recycling in convective precipitation regimes of the Fall and Spring there, when rainfall is critical for agriculture and many other human activities. We conducted simulations with WRF-ARW model at 5 km horizontal resolution, using a 1500 km x 1500 km nested grid that covers the Iberian Peninsula, with a parent domain that uses spectral nudging in order to avoid the distortion of the large-scale circulation caused by the interaction of the modeled flow with the lateral boundaries of the nested grid. For land-surface interactions we coupled WRF with the LEAF-HYDRO land surface model, which includes water table dynamics. We use therefore a tool that simulates the entire water cycle, including the water table, which has been reported to be critical for soil moisture dynamics in semi-arid regions like the Iberian Peninsula. For each one of the events that we selected, we performed two simulations: a control one, where all land-atmosphere feedbacks are taken into account, and the experiment, where infiltration of the precipitated water into the soil was suppressed. In this manner we explore the role of upward latent and sensible heat fluxes and evapotranspiration in precipitation dynamics. Preliminary results suggest that water recycling is a key factor in extending convective precipitation during several days, and that the total new water added in the area as a whole is only a fraction of the total measured rainfall. An estimation of this fraction is very important to better understanding the water budget and for hydrological planning in this water-stressed region.

Anthropogenic Land-use Change and the Dynamics of Amazon Forest Biomass

NASA Technical Reports Server (NTRS)

Laurance, William F.

2004-01-01

This project was focused on assessing the effects of prevailing land uses, such as habitat fragmentation, selective logging, and fire, on biomass and carbon storage in Amazonian forests, and on the dynamics of carbon sequestration in regenerating forests. Ancillary goals included developing GIs models to help predict the future condition of Amazonian forests, and assessing the effects of anthropogenic climate change and ENS0 droughts on intact and fragmented forests. Ground-based studies using networks of permanent plots were linked with remote-sensing data (including Landsat TM and AVHRR) at regional scales, and higher-resolution techniques (IKONOS imagery, videography, LIDAR, aerial photographs) at landscape and local scales. The project s specific goals were quite eclectic and included: Determining the effects of habitat fragmentation on forest dynamics, floristic composition, and the various components of above- and below-ground biomass. Assessing historical and physical factors that affect trajectories of forest regeneration and carbon sequestration on abandoned lands. Extrapolating results from local studies of biomass dynamics in fragmented and regenerating forests to landscape and regional scales in Amazonia, using remote sensing and GIS. Testing the hypothesis that intact Amazonian forests are functioning as a significant carbon sink. Examining destructive synergisms between forest fragmentation and fire. Assessing the short-term impacts of selective logging on aboveground biomass. Developing GIS models that integrate current spatial data on forest cover, deforestation, logging, mining, highway and roads, navigable rivers, vulnerability to wild fires, protected areas, and existing and planned infrastructure projects, in an effort to predict the future condition of Brazilian Amazonian forests over the next 20-25 years. Devising predictive spatial models to assess the influence of varied biophysical and anthropogenic predictors on Amazonian deforestation.

Measuring and modeling changes in land-atmosphere exchanges and hydrologic response in forests undergoing insect-driven mortality

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Brooks, P. D.; Harpold, A. A.; Ewers, B. E.; Pendall, E.; Barnard, H. R.; Reed, D.; Harley, P. C.; Hu, J.; Biederman, J.

2010-12-01

Given the magnitude and spatial extent of recent forest mortality in the western U.S. there is a pressing need to improve representation of such influences on the exchange of energy, water, biogeochemical and momentum fluxes in land-atmosphere parameterizations coupled to weather and climate models. In this talk we present observational data and model results from a new study aimed at improving understanding the impacts of mountain pine beetle-induced forest mortality in the central Rocky Mountains. Baseline observations and model runs from undisturbed lodgepole pine forest conditions are developed as references against which new observations and model runs from infested stands are compared. We will specifically look at the structure and evolution of sub-canopy energy exchange variables such as shortwave and longwave radiation and sub-canopy turbulence as well as sub-canopy precipitation, sapflow fluxes, canopy-scale fluxes and soil moisture and temperature. In this manner we seek to lay the ground work for evaluating the recent generation of land surface model changes aimed at representing insect-related forest dynamics in the CLM-C/N and Noah land surface models.

Multibody Modeling and Simulation for the Mars Phoenix Lander Entry, Descent and Landing

NASA Technical Reports Server (NTRS)

Queen, Eric M.; Prince, Jill L.; Desai, Prasun N.

2008-01-01

A multi-body flight simulation for the Phoenix Mars Lander has been developed that includes high fidelity six degree-of-freedom rigid-body models for the parachute and lander system. The simulation provides attitude and rate history predictions of all bodies throughout the flight, as well as loads on each of the connecting lines. In so doing, a realistic behavior of the descending parachute/lander system dynamics can be simulated that allows assessment of the Phoenix descent performance and identification of potential sensitivities for landing. This simulation provides a complete end-to-end capability of modeling the entire entry, descent, and landing sequence for the mission. Time histories of the parachute and lander aerodynamic angles are presented. The response of the lander system to various wind models and wind shears is shown to be acceptable. Monte Carlo simulation results are also presented.

Impacts of Climate Change on Biofuels Production

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

Melillo, Jerry M.

2014-04-30

The overall goal of this research project was to improve and use our biogeochemistry model, TEM, to simulate the effects of climate change and other environmental changes on the production of biofuel feedstocks. We used the improved version of TEM that is coupled with the economic model, EPPA, a part of MIT’s Earth System Model, to explore how alternative uses of land, including land for biofuels production, can help society meet proposed climate targets. During the course of this project, we have made refinements to TEM that include development of a more mechanistic plant module, with improved ecohydrology and considerationmore » of plant-water relations, and a more detailed treatment of soil nitrogen dynamics, especially processes that add or remove nitrogen from ecosystems. We have documented our changes to TEM and used the model to explore the effects on production in land ecosystems, including changes in biofuels production.« less

Acceleration Measurements During Landing in Rough Water of a 1/7-Scale Dynamic Model of Grumman XJR2F-1 Amphibian - Langley Tank Model 212, TED No. NACA 2378

NASA Technical Reports Server (NTRS)

Land, Norman S.; Zeck, Howard

1947-01-01

Tests of a 1/7 size model of the Grumman XJR2F-1 amphibian were made in Langley tank no.1 to examine the landing behavior in rough water and to measure the normal and angular accelerations experienced by the model during these landings. All landings were made normal to the direction of wave advance, a condition assumed to produce the greatest accelerations. Wave heights of 4.4 and 8.0 inches (2.5 and 4.7 ft, full size) were used in the tests and the wave lengths were varied between 10 and 50 feet (70 and 350 ft, full size). Maximum normal accelerations of about 6.5g were obtained in 4.4 inch waves and 8.5g were obtained in 8.0 inch waves. A maximum angular acceleration corresponding to 16 radians per second per second, full size, was obtained in the higher waves. The data indicate that the airplane will experience its greatest accelerations when landing in waves of about 20 feet (140 ft, full size) in length.

An analysis of the carbon balance of the Arctic Basin from 1997 to 2006

Treesearch

A.D. McGuire; D.J. Hayes; D.W. Kicklighter; M. Manizza; Q. Zhuang; M. Chen; M.J. Follows; K.R. Gurney; J.W. McClelland; J.M. Melillo; B.J. Peterson; R.G. Prinn

2010-01-01

This study used several model-based tools to analyze the dynamics of the Arctic Basin between 1997 and 2006 as a linked system of land-ocean-atmosphere C exchange. The analysis estimates that terrestrial areas of the Arctic Basin lost 62.9 Tg C yr-1 and that the Arctic Ocean gained 94.1 Tg C yr-1. Arctic lands and oceans...

Change in agricultural land use constrains adaptation of national wildlife refuges to climate change

USGS Publications Warehouse

Hamilton, Christopher M.; Thogmartin, Wayne E.; Radeloff, Volker C.; Plantinga, Andrew J.; Heglund, Patricia J.; Martinuzzi, Sebastian; Pidgeon, Anna M.

2015-01-01

Land-use change around protected areas limits their ability to conserve biodiversity by altering ecological processes such as natural hydrologic and disturbance regimes, facilitating species invasions, and interfering with dispersal of organisms. This paper informs USA National Wildlife Refuge System conservation planning by predicting future land-use change on lands within 25 km distance of 461 refuges in the USA using an econometric model. The model contained two differing policy scenarios, namely a ‘business-as-usual’ scenario and a ‘pro-agriculture’ scenario. Regardless of scenario, by 2051, forest cover and urban land use were predicted to increase around refuges, while the extent of range and pasture was predicted to decrease; cropland use decreased under the business-as-usual scenario, but increased under the pro-agriculture scenario. Increasing agricultural land value under the pro-agriculture scenario slowed an expected increase in forest around refuges, and doubled the rate of range and pasture loss. Intensity of land-use change on lands surrounding refuges differed by regions. Regional differences among scenarios revealed that an understanding of regional and local land-use dynamics and management options was an essential requirement to effectively manage these conserved lands. Such knowledge is particularly important given the predicted need to adapt to a changing global climate.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Land-use and carbon cycle responses to moderate climate change: implications for land-based mitigation?

PubMed

Humpenöder, Florian; Popp, Alexander; Stevanovic, Miodrag; Müller, Christoph; Bodirsky, Benjamin Leon; Bonsch, Markus; Dietrich, Jan Philipp; Lotze-Campen, Hermann; Weindl, Isabelle; Biewald, Anne; Rolinski, Susanne

2015-06-02

Climate change has impacts on agricultural yields, which could alter cropland requirements and hence deforestation rates. Thus, land-use responses to climate change might influence terrestrial carbon stocks. Moreover, climate change could alter the carbon storage capacity of the terrestrial biosphere and hence the land-based mitigation potential. We use a global spatially explicit economic land-use optimization model to (a) estimate the mitigation potential of a climate policy that provides economic incentives for carbon stock conservation and enhancement, (b) simulate land-use and carbon cycle responses to moderate climate change (RCP2.6), and (c) investigate the combined effects throughout the 21st century. The climate policy immediately stops deforestation and strongly increases afforestation, resulting in a global mitigation potential of 191 GtC in 2100. Climate change increases terrestrial carbon stocks not only directly through enhanced carbon sequestration (62 GtC by 2100) but also indirectly through less deforestation due to higher crop yields (16 GtC by 2100). However, such beneficial climate impacts increase the potential of the climate policy only marginally, as the potential is already large under static climatic conditions. In the broader picture, this study highlights the importance of land-use dynamics for modeling carbon cycle responses to climate change in integrated assessment modeling.

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-Use Impacts on the Terrestrial Carbon Cycle: An Integrative Tool for Resource Assessment and Planning

NASA Astrophysics Data System (ADS)

Sleeter, B. M.; Liu, J.; Zhu, Z.; Hawbaker, T. J.

2014-12-01

Human land use and natural processes contribute to the ability of ecosystems to store and sequester carbon and offset greenhouse gas emissions. Changes in land use (e.g. agricultural cultivation, timber harvest, urban development, and other land management strategies) and natural processes (e.g. climate, wildfire, disease, storm, and insect outbreak) drive the dynamics of ecosystem carbon pools. These carbon dynamics operate at different spatial and temporal scales, making it challenging to track the changes in a single integrative framework. Landowners, managers, and policy makers require data, information, and tools on the relative contributions of these drivers of ecosystem carbon stocks and fluxes in order to evaluate alternative policies and management strategies designed to increase carbon storage and sequestration. In this paper we explore preliminary results from efforts to simulate changes in ecosystem carbon at ecoregional scales, resulting from anthropogenic land use, wildfire, natural vegetation change, and climate variability under a range of future conditions coherent with a range of global change scenarios. Simulations track the fate of carbon across several pools, including living biomass, deadwood, litter, soil, and wood products. Carbon fluxes are estimated based on simulations from the Integrated Biosphere Simulator model (IBIS). Downscaled land-use projections from the Special Report on Emission Scenarios and Representative Concentration Pathways drive changes in land use, along with extrapolations based on local-scale data. We discuss the sensitivity of the model to individual drivers, and the overall uncertainty associated with the wide range of scenario projections, as well as explore alternative policy and management outcomes and their ability to increase carbon storage in terrestrial ecosystems.

Multicriteria evaluation of discharge simulation in Dynamic Global Vegetation Models

NASA Astrophysics Data System (ADS)

Yang, Hui; Piao, Shilong; Zeng, Zhenzhong; Ciais, Philippe; Yin, Yi; Friedlingstein, Pierre; Sitch, Stephen; Ahlström, Anders; Guimberteau, Matthieu; Huntingford, Chris; Levis, Sam; Levy, Peter E.; Huang, Mengtian; Li, Yue; Li, Xiran; Lomas, Mark R.; Peylin, Philippe; Poulter, Ben; Viovy, Nicolas; Zaehle, Soenke; Zeng, Ning; Zhao, Fang; Wang, Lei

2015-08-01

In this study, we assessed the performance of discharge simulations by coupling the runoff from seven Dynamic Global Vegetation Models (DGVMs; LPJ, ORCHIDEE, Sheffield-DGVM, TRIFFID, LPJ-GUESS, CLM4CN, and OCN) to one river routing model for 16 large river basins. The results show that the seasonal cycle of river discharge is generally modeled well in the low and middle latitudes but not in the high latitudes, where the peak discharge (due to snow and ice melting) is underestimated. For the annual mean discharge, the DGVMs chained with the routing model show an underestimation. Furthermore, the 30 year trend of discharge is also underestimated. For the interannual variability of discharge, a skill score based on overlapping of probability density functions (PDFs) suggests that most models correctly reproduce the observed variability (correlation coefficient higher than 0.5; i.e., models account for 50% of observed interannual variability) except for the Lena, Yenisei, Yukon, and the Congo river basins. In addition, we compared the simulated runoff from different simulations where models were forced with either fixed or varying land use. This suggests that both seasonal and annual mean runoff has been little affected by land use change but that the trend itself of runoff is sensitive to land use change. None of the models when considered individually show significantly better performances than any other and in all basins. This suggests that based on current modeling capability, a regional-weighted average of multimodel ensemble projections might be appropriate to reduce the bias in future projection of global river discharge.

Land management in the American southwest: a state-and-transition approach to ecosystem complexity.

PubMed

Bestelmeyer, Brandon T; Herrick, Jeffrey E; Brown, Joel R; Trujillo, David A; Havstad, Kris M

2004-07-01

State-and-transition models are increasingly being used to guide rangeland management. These models provide a relatively simple, management-oriented way to classify land condition (state) and to describe the factors that might cause a shift to another state (a transition). There are many formulations of state-and-transition models in the literature. The version we endorse does not adhere to any particular generalities about ecosystem dynamics, but it includes consideration of several kinds of dynamics and management response to them. In contrast to previous uses of state-and-transition models, we propose that models can, at present, be most effectively used to specify and qualitatively compare the relative benefits and potential risks of different management actions (e.g., fire and grazing) and other factors (e.g., invasive species and climate change) on specified areas of land. High spatial and temporal variability and complex interactions preclude the meaningful use of general quantitative models. Forecasts can be made on a case-by-case basis by interpreting qualitative and quantitative indicators, historical data, and spatially structured monitoring data based on conceptual models. We illustrate how science- based conceptual models are created using several rangeland examples that vary in complexity. In doing so, we illustrate the implications of designating plant communities and states in models, accounting for varying scales of pattern in vegetation and soils, interpreting the presence of plant communities on different soils and dealing with our uncertainty about how those communities were assembled and how they will change in the future. We conclude with observations about how models have helped to improve management decision-making.

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

PubMed

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

2015-05-01

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

Changing crops in response to climate: virtual Nang Rong, Thailand in an agent based simulation

PubMed Central

Malanson, George P.; Verdery, Ashton M.; Walsh, Stephen J.; Sawangdee, Yothin; Heumann, Benjamin W.; McDaniel, Philip M.; Frizzelle, Brian G.; Williams, Nathalie E.; Yao, Xiaozheng; Entwisle, Barbara; Rindfuss, Ronald R.

2014-01-01

The effects of extended climatic variability on agricultural land use were explored for the type of system found in villages of northeastern Thailand. An agent based model developed for the Nang Rong district was used to simulate land allotted to jasmine rice, heavy rice, cassava, and sugar cane. The land use choices in the model depended on likely economic outcomes, but included elements of bounded rationality in dependence on household demography. The socioeconomic dynamics are endogenous in the system, and climate changes were added as exogenous drivers. Villages changed their agricultural effort in many different ways. Most villages reduced the amount of land under cultivation, primarily with reduction in jasmine rice, but others did not. The variation in responses to climate change indicates potential sensitivity to initial conditions and path dependence for this type of system. The differences between our virtual villages and the real villages of the region indicate effects of bounded rationality and limits on model applications. PMID:25061240

Contemporary carbon dynamics in terrestrial ecosystems in the Southeastern Plains of the United States

USGS Publications Warehouse

Liu, S.; Loveland, Thomas R.; Kurtz, R.M.

2004-01-01

Quantifying carbon dynamics over large areas is frequently hindered by the lack of consistent, high-quality, spatially explicit land use and land cover change databases and appropriate modeling techniques. In this paper, we present a generic approach to address some of these challenges. Land cover change information in the Southeastern Plains ecoregion was derived from Landsat data acquired in 1973, 1980, 1986, 1992, and 2000 within 11 randomly located 20-km × 20-km sample blocks. Carbon dynamics within each of the sample blocks was simulated using the General Ensemble Biogeochemical Modeling System (GEMS), capable of assimilating the variances and covariance of major input variables into simulations using an ensemble approach. Results indicate that urban and forest areas have been increasing, whereas agricultural land has been decreasing since 1973. Forest clear-cutting activity has intensified, more than doubling from 1973 to 2000. The Southeastern Plains has been acting as a carbon sink since 1973, with an average rate of 0.89 Mg C/ha/yr. Biomass, soil organic carbon (SOC), and harvested materials account for 56%, 34%, and 10% of the sink, respectively. However, the sink has declined continuously during the same period owing to forest aging in the northern part of the ecoregion and increased forest clear-cutting activities in the south. The relative contributions to the sink from SOC and harvested materials have increased, implying that these components deserve more study in the future. The methods developed here can be used to quantify the impacts of human management activities on the carbon cycle at landscape to global scales.

Assessment of NASA's Physiographic and Meteorological Datasets as Input to HSPF and SWAT Hydrological Models

NASA Technical Reports Server (NTRS)

Alacron, Vladimir J.; Nigro, Joseph D.; McAnally, William H.; OHara, Charles G.; Engman, Edwin Ted; Toll, David

2011-01-01

This paper documents the use of simulated Moderate Resolution Imaging Spectroradiometer land use/land cover (MODIS-LULC), NASA-LIS generated precipitation and evapo-transpiration (ET), and Shuttle Radar Topography Mission (SRTM) datasets (in conjunction with standard land use, topographical and meteorological datasets) as input to hydrological models routinely used by the watershed hydrology modeling community. The study is focused in coastal watersheds in the Mississippi Gulf Coast although one of the test cases focuses in an inland watershed located in northeastern State of Mississippi, USA. The decision support tools (DSTs) into which the NASA datasets were assimilated were the Soil Water & Assessment Tool (SWAT) and the Hydrological Simulation Program FORTRAN (HSPF). These DSTs are endorsed by several US government agencies (EPA, FEMA, USGS) for water resources management strategies. These models use physiographic and meteorological data extensively. Precipitation gages and USGS gage stations in the region were used to calibrate several HSPF and SWAT model applications. Land use and topographical datasets were swapped to assess model output sensitivities. NASA-LIS meteorological data were introduced in the calibrated model applications for simulation of watershed hydrology for a time period in which no weather data were available (1997-2006). The performance of the NASA datasets in the context of hydrological modeling was assessed through comparison of measured and model-simulated hydrographs. Overall, NASA datasets were as useful as standard land use, topographical , and meteorological datasets. Moreover, NASA datasets were used for performing analyses that the standard datasets could not made possible, e.g., introduction of land use dynamics into hydrological simulations

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Technical Reports Server (NTRS)

Koster, Randal; Walker, G.; Thornton, Patti; Collatz, G. J.

2012-01-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Astrophysics Data System (ADS)

Koster, R. D.; Walker, G.; Thornton, P. E.; Collatz, G. J.

2012-12-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if somewhat biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

The role of evapotranspiration fluxes in summertime precipitation in Central Europe: coupled groundwater-atmosphere simulations with the WRF-LEAFHYDRO system.

NASA Astrophysics Data System (ADS)

Regueiro Sanfiz, Sabela; Gómez, Breo; Miguez Macho, Gonzalo

2017-04-01

Because of its continental position, Central Europe summertime rainfall is largely dependent on local or regional dynamics, with precipitation water possibly also significantly dependent on local sources. We investigate here land-atmosphere feedbacks over inland Europe focusing in particular on evapotranspiration-soil moisture connections and precipitation recycling ratios. For this purpose, a set of simulations were performed with the Weather Research and Forecasting (WRF) model coupled to LEAFHYDRO soil-vegetation-hydrology model. The LEAFHYDRO Land Surface Model includes a groundwater parameterization with a dynamic water table fully coupling groundwater to the soil-vegetation and surface waters via two-way fluxes. A water tagging capability in the WRF model is used to quantify evapotranspiration contribution to precipitation over the region. Several years are considered, including summertime 2002, during which severe flooding occurred. Preliminary results from our simulations highlight the link of large areas with shallow water with high air moisture values through the summer season; and the importance of the contribution of evapotranspiration to summertime precipitation. Consequently, results show the advantages of using a fully coupled hydrology-atmospheric modeling system.

Assured crew return vehicle post landing configuration design and test

NASA Technical Reports Server (NTRS)

1992-01-01

The 1991-1992 senior Mechanical and Aerospace Engineering Design class continued work on the post landing configurations for the Assured Crew Return Vehicle (ACRV) and the Emergency Egress Couch (EEC). The ACRV will be permanently docked to Space Station Freedom fulfilling NASA's commitment of Assured Crew Return Capability in the event of an accident or illness aboard Space Station Freedom. The EEC provides medical support and a transportation surface for an incapacitated crew member. The objective of the projects was to give the ACRV Project Office data to feed into their feasibility studies. Four design teams were given the task of developing models with dynamically and geometrically scaled characteristics. Groups one and two combined efforts to design a one-fifth scale model for the Apollo Command Module derivative, an on-board flotation system, and a lift attachment point system. This model was designed to test the feasibility of a rigid flotation and stabilization system and to determine the dynamics associated with lifting the vehicle during retrieval. However, due to priorities, it was not built. Group three designed a one-fifth scale model of the Johnson Space Center (JSC) benchmark configuration, the Station Crew Return Alternative Module (SCRAM) with a lift attachment point system. This model helped to determine the flotation and lifting characteristics of the SCRAM configuration. Group four designed a full scale EEC with changeable geometric and geometric and dynamic characteristics. This model provided data on the geometric characteristics of the EEC and on the placement of the CG and moment of inertia. It also gave the helicopter rescue personnel direct input to the feasibility study. Section 1 describes in detail the design of a one-fifth scale model of the Apollo Command Module Derivative (ACMD) ACRV. The objective of the ACMD Configuration Model Team was to use geometric and dynamic constraints to design a one-fifth scale working model of the Apollo Command Module Derivative (ACMD) configuration with a Lift Attachment Point (LAP) System. This model was required to incorporate a rigidly mounted flotation system and the egress system designed the previous academic year. The LAP system was to be used to determine the dynamic effects of locating the lifting points at different locations on the vehicle. The team was then to build and test the model; however, due to priorities, this did not occur. To better simulate the ACMD after a water landing, the nose cone section was removed and the deck area exposed. The areas researched during the design process were construction, center of gravity and moment of inertia, and lift attachment points.

The Study of Driving Forces of Land Use Transformation in the Pearl River Delta during 1990 to 2010※

NASA Astrophysics Data System (ADS)

Yang, Kun; Wang, Xiuming; Zhao, Peng; Liu, Xucheng; Zhang, Yuhuan

2018-05-01

Based on the land use data of the study area in 1990, 2000 and 2010, the paper tries to analyse the characteristic of land use and cover change (LUCC) in Pearl River Delta and its driving forces as well as the differences of driving forces among Shenzhen, Dongguan and Foshan by adopting the approaches of land use dynamic degree, the land use transition matrix and case studies. The results show that a large amount of farmland and forests have been converted to construction land in the study area, and the synthesize land use dynamic degrees of the study area are 2.3% and 6.2% during 1990-2000 and 2000-2010, respectively. The results also indicate that Zhuhai and Shenzhen have the highest land use dynamic degree among the nine cities of Pearl River Delta during 1990-2000, and Dongguan has the highest land use dynamic degree during 2000-2010. It can be inferred that the transitions from farmland and forest to construction land have been propelled by the local economic development and population growth, and the land use changes in forest and grassland have been driven by natural factors such as slope and elevation.

An eleven-year validation of a physically-based distributed dynamic ecohydorological model tRIBS+VEGGIE: Walnut Gulch Experimental Watershed

NASA Astrophysics Data System (ADS)

Sivandran, G.; Bisht, G.; Ivanov, V. Y.; Bras, R. L.

2008-12-01

A coupled, dynamic vegetation and hydrologic model, tRIBS+VEGGIE, was applied to the semiarid Walnut Gulch Experimental Watershed in Arizona. The physically-based, distributed nature of the coupled model allows for parameterization and simulation of watershed vegetation-water-energy dynamics on timescales varying from hourly to interannual. The model also allows for explicit spatial representation of processes that vary due to complex topography, such as lateral redistribution of moisture and partitioning of radiation with respect to aspect and slope. Model parameterization and forcing was conducted using readily available databases for topography, soil types, and land use cover as well as the data from network of meteorological stations located within the Walnut Gulch watershed. In order to test the performance of the model, three sets of simulations were conducted over an 11 year period from 1997 to 2007. Two simulations focus on heavily instrumented nested watersheds within the Walnut Gulch basin; (i) Kendall watershed, which is dominated by annual grasses; and (ii) Lucky Hills watershed, which is dominated by a mixture of deciduous and evergreen shrubs. The third set of simulations cover the entire Walnut Gulch Watershed. Model validation and performance were evaluated in relation to three broad categories; (i) energy balance components: the network of meteorological stations were used to validate the key energy fluxes; (ii) water balance components: the network of flumes, rain gauges and soil moisture stations installed within the watershed were utilized to validate the manner in which the model partitions moisture; and (iii) vegetation dynamics: remote sensing products from MODIS were used to validate spatial and temporal vegetation dynamics. Model results demonstrate satisfactory spatial and temporal agreement with observed data, giving confidence that key ecohydrological processes can be adequately represented for future applications of tRIBS+VEGGIE in regional modeling of land-atmosphere interactions.

A spatial socio-ecosystem approach to analyse human-environment interactions on climate change adaptation for water resources management

NASA Astrophysics Data System (ADS)

Giupponi, Carlo; Mojtahed, Vahid

2017-04-01

Global climate and socio-economic drivers determine the future patterns of the allocation and the trade of resources and commodities in all markets. The agricultural sector is an emblematic case in which natural (e.g. climate), social (e.g. demography) and economic (e.g. the market) drivers of change interact, determining the evolution of social and ecological systems (or simply socio-ecosystems; SES) over time. In order to analyse the dynamics and possible future evolutions of SES, the combination of local complex systems and global drivers and trends require the development of multiscale approaches. At global level, climatic general circulation models (CGM) and computable general equilibrium or partial equilibrium models have been used for many years to explore the effects of global trends and generate future climate and socio-economic scenarios. Al local level, the inherent complexity of SESs and their spatial and temporal variabilities require different modelling approaches of physical/environmental sub-systems (e.g. field scale crop modelling, GIS-based models, etc.) and of human agency decision makers (e.g. agent based models). Global and local models have different assumption, limitations, constrains, etc., but in some cases integration is possible and several attempts are in progress to couple different models within the so-called Integrated Assessment Models. This work explores an innovative proposal to integrate the global and local approaches, where agent-based models (ABM) are used to simulate spatial (i.e. grid-based) and temporal dynamics of land and water resource use spatial and temporal dynamics, under the effect of global drivers. We focus in particular on how global change may affect land-use allocation at the local to regional level, under the influence of limited natural resources, land and water in particular. We specifically explore how constrains and competition for natural resources may induce non-linearities and discontinuities in socio-ecosystems behaviour. Our general ambition is to explore the feasibility of an approach that could be implemented worldwide through the identification of representative cases described by means of spatially explicit integrated simulations in communication with global modelling. Our specific objective is to test how ABMs can support scenario analysis at regional scale, and in particular how this can facilitate understanding of the role of human agency and its behavioural characteristics in local to global dynamics. The SES of interest is the agro-ecosystem with its relationships with other land uses. In order to test the feasibility of application at global level, all the information about land uses, natural resources, local climate, crop potential productions, etc. were derived from freely available spatial data sets covering the whole planet, which provided the ABM model with spatial information as matrices of pixels. Input maps were extracted from the Global Agro-Ecological Zone (GAEZ) web site of the Food and Agriculture Organization of the United Nations and compiled in the local GIS from where they were then converted in a format compatible with Matlab. In this initial application, an ABM prototype was developed in three test areas around the Mediterranean Basin, in agricultural regions of Tunisia, Italy and Spain.

Wind modeling and lateral control for automatic landing

NASA Technical Reports Server (NTRS)

Holley, W. E.; Bryson, A. E., Jr.

1975-01-01

For the purposes of aircraft control system design and analysis, the wind can be characterized by a mean component which varies with height and by turbulent components which are described by the von Karman correlation model. The aircraft aero-dynamic forces and moments depend linearly on uniform and gradient gust components obtained by averaging over the aircraft's length and span. The correlations of the averaged components are then approximated by the outputs of linear shaping filters forced by white noise. The resulting model of the crosswind shear and turbulence effects is used in the design of a lateral control system for the automatic landing of a DC-8 aircraft.

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.

Changing Amazon biomass and the role of atmospheric CO2 concentration, climate, and land use

NASA Astrophysics Data System (ADS)

Almeida Castanho, Andrea D.; Galbraith, David; Zhang, Ke; Coe, Michael T.; Costa, Marcos H.; Moorcroft, Paul

2016-01-01

The Amazon tropical evergreen forest is an important component of the global carbon budget. Its forest floristic composition, structure, and function are sensitive to changes in climate, atmospheric composition, and land use. In this study biomass and productivity simulated by three dynamic global vegetation models (Integrated Biosphere Simulator, Ecosystem Demography Biosphere Model, and Joint UK Land Environment Simulator) for the period 1970-2008 are compared with observations from forest plots (Rede Amazónica de Inventarios Forestales). The spatial variability in biomass and productivity simulated by the DGVMs is low in comparison to the field observations in part because of poor representation of the heterogeneity of vegetation traits within the models. We find that over the last four decades the CO2 fertilization effect dominates a long-term increase in simulated biomass in undisturbed Amazonian forests, while land use change in the south and southeastern Amazonia dominates a reduction in Amazon aboveground biomass, of similar magnitude to the CO2 biomass gain. Climate extremes exert a strong effect on the observed biomass on short time scales, but the models are incapable of reproducing the observed impacts of extreme drought on forest biomass. We find that future improvements in the accuracy of DGVM predictions will require improved representation of four key elements: (1) spatially variable plant traits, (2) soil and nutrients mediated processes, (3) extreme event mortality, and (4) sensitivity to climatic variability. Finally, continued long-term observations and ecosystem-scale experiments (e.g. Free-Air CO2 Enrichment experiments) are essential for a better understanding of the changing dynamics of tropical forests.

Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

NASA Astrophysics Data System (ADS)

Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

2017-09-01

With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. V.; Yerazunis, S. W.

1973-01-01

Problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars are reported. Problem areas include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis, terrain modeling and path selection; and chemical analysis of specimens. These tasks are summarized: vehicle model design, mathematical model of vehicle dynamics, experimental vehicle dynamics, obstacle negotiation, electrochemical controls, remote control, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer subsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, and chromatograph model evaluation and improvement.

Land-use change in oil palm dominated tropical landscapes-An agent-based model to explore ecological and socio-economic trade-offs.

PubMed

Dislich, Claudia; Hettig, Elisabeth; Salecker, Jan; Heinonen, Johannes; Lay, Jann; Meyer, Katrin M; Wiegand, Kerstin; Tarigan, Suria

2018-01-01

Land-use changes have dramatically transformed tropical landscapes. We describe an ecological-economic land-use change model as an integrated, exploratory tool used to analyze how tropical land-use change affects ecological and socio-economic functions. The model analysis seeks to determine what kind of landscape mosaic can improve the ensemble of ecosystem functioning, biodiversity, and economic benefit based on the synergies and trade-offs that we have to account for. More specifically, (1) how do specific ecosystem functions, such as carbon storage, and economic functions, such as household consumption, relate to each other? (2) How do external factors, such as the output prices of crops, affect these relationships? (3) How do these relationships change when production inefficiency differs between smallholder farmers and learning is incorporated? We initialize the ecological-economic model with artificially generated land-use maps parameterized to our study region. The economic sub-model simulates smallholder land-use management decisions based on a profit maximization assumption. Each household determines factor inputs for all household fields and decides on land-use change based on available wealth. The ecological sub-model includes a simple account of carbon sequestration in above-ground and below-ground vegetation. We demonstrate model capabilities with results on household consumption and carbon sequestration from different output price and farming efficiency scenarios. The overall results reveal complex interactions between the economic and ecological spheres. For instance, model scenarios with heterogeneous crop-specific household productivity reveal a comparatively high inertia of land-use change. Our model analysis even shows such an increased temporal stability in landscape composition and carbon stocks of the agricultural area under dynamic price trends. These findings underline the utility of ecological-economic models, such as ours, to act as exploratory tools which can advance our understanding of the mechanisms underlying the trade-offs and synergies of ecological and economic functions in tropical landscapes.

Land-use change in oil palm dominated tropical landscapes—An agent-based model to explore ecological and socio-economic trade-offs

PubMed Central

Dislich, Claudia; Hettig, Elisabeth; Heinonen, Johannes; Lay, Jann; Meyer, Katrin M.; Wiegand, Kerstin; Tarigan, Suria

2018-01-01

Land-use changes have dramatically transformed tropical landscapes. We describe an ecological-economic land-use change model as an integrated, exploratory tool used to analyze how tropical land-use change affects ecological and socio-economic functions. The model analysis seeks to determine what kind of landscape mosaic can improve the ensemble of ecosystem functioning, biodiversity, and economic benefit based on the synergies and trade-offs that we have to account for. More specifically, (1) how do specific ecosystem functions, such as carbon storage, and economic functions, such as household consumption, relate to each other? (2) How do external factors, such as the output prices of crops, affect these relationships? (3) How do these relationships change when production inefficiency differs between smallholder farmers and learning is incorporated? We initialize the ecological-economic model with artificially generated land-use maps parameterized to our study region. The economic sub-model simulates smallholder land-use management decisions based on a profit maximization assumption. Each household determines factor inputs for all household fields and decides on land-use change based on available wealth. The ecological sub-model includes a simple account of carbon sequestration in above-ground and below-ground vegetation. We demonstrate model capabilities with results on household consumption and carbon sequestration from different output price and farming efficiency scenarios. The overall results reveal complex interactions between the economic and ecological spheres. For instance, model scenarios with heterogeneous crop-specific household productivity reveal a comparatively high inertia of land-use change. Our model analysis even shows such an increased temporal stability in landscape composition and carbon stocks of the agricultural area under dynamic price trends. These findings underline the utility of ecological-economic models, such as ours, to act as exploratory tools which can advance our understanding of the mechanisms underlying the trade-offs and synergies of ecological and economic functions in tropical landscapes. PMID:29351290

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

Modeling daily soil salinity dynamics in response to agricultural and environmental changes in coastal Bangladesh

NASA Astrophysics Data System (ADS)

Payo, Andrés.; Lázár, Attila N.; Clarke, Derek; Nicholls, Robert J.; Bricheno, Lucy; Mashfiqus, Salehin; Haque, Anisul

2017-05-01

Understanding the dynamics of salt movement in the soil is a prerequisite for devising appropriate management strategies for land productivity of coastal regions, especially low-lying delta regions, which support many millions of farmers around the world. At present, there are no numerical models able to resolve soil salinity at regional scale and at daily time steps. In this research, we develop a novel holistic approach to simulate soil salinization comprising an emulator-based soil salt and water balance calculated at daily time steps. The method is demonstrated for the agriculture areas of coastal Bangladesh (˜20,000 km2). This shows that we can reproduce the dynamics of soil salinity under multiple land uses, including rice crops, combined shrimp and rice farming, as well as non-rice crops. The model also reproduced well the observed spatial soil salinity for the year 2009. Using this approach, we have projected the soil salinity for three different climate ensembles, including relative sea-level rise for the year 2050. Projected soil salinity changes are significantly smaller than other reported projections. The results suggest that inter-season weather variability is a key driver of salinization of agriculture soils at coastal Bangladesh.

Comparison of dynamic postural stability scores between athletes with and without chronic ankle instability during lateral jump landing.

PubMed

Shiravi, Zeinab; Shadmehr, Azadeh; Moghadam, Saeed Talebian; Moghadam, Behrouz Attarbashi

2017-01-01

Many ankle injuries occur while participating in sports that require jumping and landing such as basketball, volleyball and soccer. Most recent studies have investigated dynamic postural stability of patients with chronic ankle instability after landing from a forward jump. The present study aimed to investigate the dynamic postural stability of the athletes who suffer from chronic ankle sprain while landing from a lateral jump. Twelve athletes with self-reported unilateral chronic ankle instability (4 females and 8 males) and 12 matched controls (3 females and 9 males) voluntarily participated in the study. Dynamic postural stability index and its directional indices were measured while performing lateral jump landing test. No differences were found between athletes with and without chronic ankle instability during our landing protocol by means of the dynamic postural stability index and its directional indices. Findings showed that in each group, medial/lateral stability index is significantly higher than anterior/posterior and vertical stability indexes. Findings showed that dynamic postural stability was not significantly different between the two groups. Future studies should examine chronic ankle instability patients with more severe disabilities and expose them to more challenging dynamic balance conditions to further explore postural stability. IIIa.

Elkhorn Slough: Detecting Eutrophication through Geospatial Modeling Applications

NASA Astrophysics Data System (ADS)

Caraballo Álvarez, I. O.; Childs, A.; Jurich, K.

2016-12-01

Elkhorn Slough in Monterey, California, has experienced substantial nutrient loading and eutrophication over the past 21 years as a result of fertilizer-rich runoff from nearby agricultural fields. This study seeks to identify and track spatial patterns of eutrophication hotspots and the correlation to land use changes, possible nutrient sources, and general climatic trends using remotely sensed and in situ data. Threats of rising sea level, subsiding marshes, and increased eutrophication hotspots demonstrate the necessity to analyze the effects of increasing nutrient loads, relative sea level changes, and sedimentation within Elkhorn Slough. The Soil & Water Assessment Tool (SWAT) model integrates specified inputs to assess nutrient and sediment loading and their sources. TerrSet's Land Change Modeler forecasts the future potential of land change transitions for various land cover classes around the slough as a result of nutrient loading, eutrophication, and increased sedimentation. TerrSet's Earth Trends Modeler provides a comprehensive analysis of image time series to rapidly assess long term eutrophication trends and detect spatial patterns of known hotspots. Results from this study will inform future coastal management practices and provide greater spatial and temporal insight into Elkhorn Slough eutrophication dynamics.

Integration of Genetic Algorithms and Fuzzy Logic for Urban Growth Modeling

NASA Astrophysics Data System (ADS)

Foroutan, E.; Delavar, M. R.; Araabi, B. N.

2012-07-01

Urban growth phenomenon as a spatio-temporal continuous process is subject to spatial uncertainty. This inherent uncertainty cannot be fully addressed by the conventional methods based on the Boolean algebra. Fuzzy logic can be employed to overcome this limitation. Fuzzy logic preserves the continuity of dynamic urban growth spatially by choosing fuzzy membership functions, fuzzy rules and the fuzzification-defuzzification process. Fuzzy membership functions and fuzzy rule sets as the heart of fuzzy logic are rather subjective and dependent on the expert. However, due to lack of a definite method for determining the membership function parameters, certain optimization is needed to tune the parameters and improve the performance of the model. This paper integrates genetic algorithms and fuzzy logic as a genetic fuzzy system (GFS) for modeling dynamic urban growth. The proposed approach is applied for modeling urban growth in Tehran Metropolitan Area in Iran. Historical land use/cover data of Tehran Metropolitan Area extracted from the 1988 and 1999 Landsat ETM+ images are employed in order to simulate the urban growth. The extracted land use classes of the year 1988 include urban areas, street, vegetation areas, slope and elevation used as urban growth physical driving forces. Relative Operating Characteristic (ROC) curve as an fitness function has been used to evaluate the performance of the GFS algorithm. The optimum membership function parameter is applied for generating a suitability map for the urban growth. Comparing the suitability map and real land use map of 1999 gives the threshold value for the best suitability map which can simulate the land use map of 1999. The simulation outcomes in terms of kappa of 89.13% and overall map accuracy of 95.58% demonstrated the efficiency and reliability of the proposed model.

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.

On the global limits of bioenergy and land use for climate change mitigation

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

Strapasson, Alexandre; Woods, Jeremy; Chum, Helena

Across energy, agricultural and forestry landscapes, the production of biomass for energy has emerged as a controversial driver of land-use change. We present a novel, simple methodology, to probe the potential global sustainability limits of bioenergy over time for energy provision and climate change mitigation using a complex-systems approach for assessing land-use dynamics. Primary biomass that could provide between 70 EJ year -1 and 360 EJ year -1, globally, by 2050 was simulated in the context of different land-use futures, food diet patterns and climate change mitigation efforts. Our simulations also show ranges of potential greenhouse gas emissions for agriculture,more » forestry and other land uses by 2050, including not only above-ground biomass-related emissions, but also from changes in soil carbon, from as high as 24 GtCO 2eq year-1 to as low as minus 21 GtCO 2eq year -1, which would represent a significant source of negative emissions. Based on the modelling simulations, the discussions offer novel insights about bioenergy as part of a broader integrated system. As a result, there are sustainability limits to the scale of bioenergy provision, they are dynamic over time, being responsive to land management options deployed worldwide.« less

On the global limits of bioenergy and land use for climate change mitigation

DOE PAGES

Strapasson, Alexandre; Woods, Jeremy; Chum, Helena; ...

2017-05-24

Across energy, agricultural and forestry landscapes, the production of biomass for energy has emerged as a controversial driver of land-use change. We present a novel, simple methodology, to probe the potential global sustainability limits of bioenergy over time for energy provision and climate change mitigation using a complex-systems approach for assessing land-use dynamics. Primary biomass that could provide between 70 EJ year -1 and 360 EJ year -1, globally, by 2050 was simulated in the context of different land-use futures, food diet patterns and climate change mitigation efforts. Our simulations also show ranges of potential greenhouse gas emissions for agriculture,more » forestry and other land uses by 2050, including not only above-ground biomass-related emissions, but also from changes in soil carbon, from as high as 24 GtCO 2eq year-1 to as low as minus 21 GtCO 2eq year -1, which would represent a significant source of negative emissions. Based on the modelling simulations, the discussions offer novel insights about bioenergy as part of a broader integrated system. As a result, there are sustainability limits to the scale of bioenergy provision, they are dynamic over time, being responsive to land management options deployed worldwide.« less

Estimation of gross land-use change and its uncertainty using a Bayesian data assimilation approach

NASA Astrophysics Data System (ADS)

Levy, Peter; van Oijen, Marcel; Buys, Gwen; Tomlinson, Sam

2018-03-01

We present a method for estimating land-use change using a Bayesian data assimilation approach. The approach provides a general framework for combining multiple disparate data sources with a simple model. This allows us to constrain estimates of gross land-use change with reliable national-scale census data, whilst retaining the detailed information available from several other sources. Eight different data sources, with three different data structures, were combined in our posterior estimate of land use and land-use change, and other data sources could easily be added in future. The tendency for observations to underestimate gross land-use change is accounted for by allowing for a skewed distribution in the likelihood function. The data structure produced has high temporal and spatial resolution, and is appropriate for dynamic process-based modelling. Uncertainty is propagated appropriately into the output, so we have a full posterior distribution of output and parameters. The data are available in the widely used netCDF file format from http://eidc.ceh.ac.uk/.

Modeling and Simulation of the Second-Generation Orion Crew Module Air Bag Landing System

NASA Technical Reports Server (NTRS)

Timmers, Richard B.; Welch, Joseph V.; Hardy, Robin C.

2009-01-01

Air bags were evaluated as the landing attenuation system for earth landing of the Orion Crew Module (CM). An important element of the air bag system design process is proper modeling of the proposed configuration to determine if the resulting performance meets requirements. Analysis conducted to date shows that airbags are capable of providing a graceful landing of the CM in nominal and off-nominal conditions such as parachute failure, high horizontal winds, and unfavorable vehicle/ground angle combinations. The efforts presented here surround a second generation of the airbag design developed by ILC Dover, and is based on previous design, analysis, and testing efforts. In order to fully evaluate the second generation air bag design and correlate the dynamic simulations, a series of drop tests were carried out at NASA Langley's Landing and Impact Research (LandIR) facility. The tests consisted of a full-scale set of air bags attached to a full-scale test article representing the Orion Crew Module. The techniques used to collect experimental data, construct the simulations, and make comparisons to experimental data are discussed.

Modeling Land Use Change Impacts on Water Resources in a Tropical West African Catchment (dano, Burkina Faso)

NASA Astrophysics Data System (ADS)

Yira, Y.; Diekkrüger, B.; Steup, G.; Bossa, A. Y.

2015-12-01

This study investigates the impacts of land use change on water resources in the Dano catchment, Burkina Faso, using a physically based hydrological simulation model and land use scenarios. Land use dynamic in the catchment was assessed through the analysis of four land use maps corresponding to the land use status in 1990, 2000, 2007 and 2013. A reclassification procedure of the maps permitted to assess the major land use changes in the catchment from 1990 to 2013. The land use maps were used to build five land use scenarios corresponding to different levels of land use change in the catchment. Water balance was simulated by applying the Water flow and balance Simulation Model (WaSiM) using observed discharge, soil moisture, and groundwater level for model calibration and validation. Model statistical quality measures (R2, NSE and KGE) achieved during the calibration and the validation ranged between 0.9 and 0.6 for total discharge, soil moisture, and groundwater level, indicating satisfying to good agreements between observed and simulated variables. After a successful multi-criteria validation the model was run with the land use scenarios. The land use assessment exhibited a decrease of savannah at an annual rate of 2% since 1990. Conversely, cropland and urban areas have increased. Since urban areas occupy only 3% of the catchment in 2013 it can be assumed that savannah was mainly converted to cropland. The increase in cropland area results from the population growth and the farming system in the catchment. A clear increase in total discharge (+17%) and decrease in evapotranspiration (-5%) was observed following land use change in the catchment. A strong relationship was established between savannah degradation, cropland expansion, discharge increase and reduction of evapotranspiration. The increase in total discharge is related to high discharge and peak flow, suggesting (i) an increase in water resources that is not available for plant growth and the population of the catchment and (ii) an alteration of flood risk for both the population within and downstream of the catchment.

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

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.

Legacy nutrient dynamics and patterns of catchment response under changing land use and management

NASA Astrophysics Data System (ADS)

Attinger, S.; Van, M. K.; Basu, N. B.

2017-12-01

Watersheds are complex heterogeneous systems that store, transform, and release water and nutrients under a broad distribution of both natural and anthropogenic controls. Many current watershed models, from complex numerical models to simpler reservoir-type models, are considered to be well-developed in their ability to predict fluxes of water and nutrients to streams and groundwater. They are generally less adept, however, at capturing watershed storage dynamics. In other words, many current models are run with an assumption of steady-state dynamics, and focus on nutrient flows rather than changes in nutrient stocks within watersheds. Although these commonly used modeling approaches may be able to adequately capture short-term watershed dynamics, they are unable to represent the clear nonlinearities or hysteresis responses observed in watersheds experiencing significant changes in nutrient inputs. To address such a lack, we have, in the present work, developed a parsimonious modeling approach designed to capture long-term catchment responses to spatial and temporal changes in nutrient inputs. In this approach, we conceptualize the catchment as a biogeochemical reactor that is driven by nutrient inputs, characterized internally by both biogeochemical degradation and residence or travel time distributions, resulting in a specific nutrient output. For the model simulations, we define a range of different scenarios to represent real-world changes in land use and management implemented to improve water quality. We then introduce the concept of state-space trajectories to describe system responses to these potential changes in anthropogenic forcings. We also increase model complexity, in a stepwise fashion, by dividing the catchment into multiple biogeochemical reactors, coupled in series or in parallel. Using this approach, we attempt to answer the following questions: (1) What level of model complexity is needed to capture observed system responses? (2) How can we explain different patterns of nonlinearity in watershed nutrient dynamics? And finally, how does the accumulation of nutrient legacies within watersheds impact current and future water quality?

Soil organic carbon dynamics as related to land use history in the northwestern Great Plains

USGS Publications Warehouse

Tan, Z.; Liu, S.; Johnston, C.A.; Loveland, Thomas R.; Tieszen, L.L.; Liu, J.; Kurtz, R.

2005-01-01

Strategies for mitigating the global greenhouse effect must account for soil organic carbon (SOC) dynamics at both spatial and temporal scales, which is usually challenging owing to limitations in data and approach. This study was conducted to characterize the SOC dynamics associated with land use change history in the northwestern Great Plains ecoregion. A sampling framework (40 sample blocks of 10 × 10 km2 randomly located in the ecoregion) and the General Ensemble Biogeochemical Modeling System (GEMS) were used to quantify the spatial and temporal variability in the SOC stock from 1972 to 2001. Results indicate that C source and sink areas coexisted within the ecoregion, and the SOC stock in the upper 20-cm depth increased by 3.93 Mg ha−1 over the 29 years. About 17.5% of the area was evaluated as a C source at 122 kg C ha−1 yr−1. The spatial variability of SOC stock was attributed to the dynamics of both slow and passive fractions, while the temporal variation depended on the slow fraction only. The SOC change at the block scale was positively related to either grassland proportion or negatively related to cropland proportion. We concluded that the slow C pool determined whether soils behaved as sources or sinks of atmospheric CO2, but the strength depended on antecedent SOC contents, land cover type, and land use change history in the ecoregion.

Land-Price Dynamics Surrounding Large-Scale Land Development of Technopolis Gedebage, Bandung, Indonesia

NASA Astrophysics Data System (ADS)

Hasanawi, A.; Winarso, H.

2018-05-01

In spite of its potential value to governments, detailed information on how land prices vary spatially in a city is very lacking. Land price in the city, especially around the development activity, is not known. There are some considerable studies showing that investment in land development increases the land market price; however, only a few are found. One of them is about the impact of large-scale investment by Sumarecon in Gedebage Bandung, which is planning to develop “Technopolis”, as the second center of Bandung Municipality.This paper discusses the land-price dynamics around the Technopolis Gedebage Bandung, using information obtained from many sources including an interview with experienced brokers. Appraised prices were given for different types of residential plot distinguished by tenure, distance from the main road, and infrastructural provision. This research aims to explain the dynamics of the land price surrounding the large-scale land development. The dynamics of the land price are described by the median land price market growth using the Surfer DEM software. The data analysis in Technopolis Gedebage Bandung shows the relative importance of land location, infrastructural provision and tenure (land title) for dynamics of the land price. The examination of data makes it possible to test whether and where there has been a spiraling of land prices. This paper argues that the increasing recent price has been consistently greater in suburban plots than that in the inner city as a result of the massive demand of the large-scale land development project. The increasing price of land cannot be controlled; the market price is rising very quickly among other things due to the fact that Gedebage will become the technopolis area. This, however, can indirectly burden the lower-middle-class groups, such as they are displaced from their previous owned-land, and implicate on ever-decreasing income as the livelihood resources (such as farming and agriculture) are lost.

Simulating crop growth with Expert-N-GECROS under different site conditions in Southwest Germany

NASA Astrophysics Data System (ADS)

Poyda, Arne; Ingwersen, Joachim; Demyan, Scott; Gayler, Sebastian; Streck, Thilo

2016-04-01

When feedbacks between the land surface and the atmosphere are investigated by Atmosphere-Land surface-Crop-Models (ALCM) it is fundamental to accurately simulate crop growth dynamics as plants directly influence the energy partitioning at the plant-atmosphere interface. To study both the response and the effect of intensive agricultural crop production systems on regional climate change in Southwest Germany, the crop growth model GECROS (YIN & VAN LAAR, 2005) was calibrated based on multi-year field data from typical crop rotations in the Kraichgau and Swabian Alb regions. Additionally, the SOC (soil organic carbon) model DAISY (MÜLLER et al., 1998) was implemented in the Expert-N model tool (ENGEL & PRIESACK, 1993) and combined with GECROS. The model was calibrated based on a set of plant (BBCH, LAI, plant height, aboveground biomass, N content of biomass) and weather data for the years 2010 - 2013 and validated with the data of 2014. As GECROS adjusts the root-shoot partitioning in response to external conditions (water, nitrogen, CO2), it is suitable to simulate crop growth dynamics under changing climate conditions and potentially more frequent stress situations. As C and N pools and turnover rates in soil as well as preceding crop effects were expected to considerably influence crop growth, the model was run in a multi-year, dynamic way. Crop residues and soil mineral N (nitrate, ammonium) available for the subsequent crop were accounted for. The model simulates growth dynamics of winter wheat, winter rape, silage maize and summer barley at the Kraichgau and Swabian Alb sites well. The Expert-N-GECROS model is currently parameterized for crops with potentially increasing shares in future crop rotations. First results will be shown.

Comparison of closed loop model with flight test results

NASA Technical Reports Server (NTRS)

George, F. L.

1981-01-01

An analytic technique capable of predicting the landing characteristics of proposed aircraft configurations in the early stages of design was developed. In this analysis, a linear pilot-aircraft closed loop model was evaluated using experimental data generated with the NT-33 variable stability in-flight simulator. The pilot dynamics are modeled as inner and outer servo loop closures around aircraft pitch attitude, and altitude rate-of-change respectively. The landing flare maneuver is of particular interest as recent experience with military and other highly augmented vehicles shows this task to be relatively demanding, and potentially a critical design point. A unique feature of the pilot model is the incorporation of an internal model of the pilot's desired flight path for the flare maneuver.

SPRUCE Representing Northern Peatland Microtopography and Hydrology within the Community Land Model: Modeling Archive

DOE Data Explorer

Shi, X. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Thornton, P. E. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Ricciuto, D. M. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Hanson, P. J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Mao, J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Sebestyen, S. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Griffiths, N. A. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Bisht, G. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.

2016-09-01

Here we provide model code, inputs, outputs and evaluation datasets for a new configuration of the Community Land Model (CLM) for SPRUCE, which includes a fully prognostic water table calculation for SPRUCE. Our structural and process changes to CLM focus on modifications needed to represent the hydrologic cycle of bogs environment with perched water tables, as well as distinct hydrologic dynamics and vegetation communities of the raised hummock and sunken hollow microtopography characteristic of SPRUCE and other peatland bogs. The modified model was parameterized and independently evaluated against observations from an ombrotrophic raised-dome bog in northern Minnesota (S1-Bog), the site for the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE).

Tank Investigation of a Powered Dynamic Model of a Large Long-Range Flying Boat

NASA Technical Reports Server (NTRS)

Parkinson, John B; Olson, Roland E; Harr, Marvin I

1947-01-01

Principles for designing the optimum hull for a large long-range flying boat to meet the requirements of seaworthiness, minimum drag, and ability to take off and land at all operational gross loads were incorporated in a 1/12-size powered dynamic model of a four-engine transport flying boat having a design gross load of 165,000 pounds. These design principles included the selection of a moderate beam loading, ample forebody length, sufficient depth of step, and close adherence to the form of a streamline body. The aerodynamic and hydrodynamic characteristics of the model were investigated in Langley tank no. 1. Tests were made to determine the minimum allowable depth of step for adequate landing stability, the suitability of the fore-and-aft location of the step, the take-off performance, the spray characteristics, and the effects of simple spray-control devices. The application of the design criterions used and test results should be useful in the preliminary design of similar large flying boats.

Landing Energy Dissipation for Manned Reentry Vehicles

NASA Technical Reports Server (NTRS)

Fisher, Lloyd J., Jr.

1960-01-01

Analytical and experimental investigations have been made to determine the landing-energy-dissipation characteristics for several types of landing gear for manned reentry vehicles. The landing vehicles are considered in two categories: those having essentially vertical-descent paths, the parachute-supported vehicles, and those having essentially horizontal paths, the lifting vehicles. The energy-dissipation devices discussed are crushable materials such as foamed plastics and honeycomb for internal application in couch-support systems, yielding metal elements as part of the structure of capsules or as alternates for oleos in landing-gear struts, inflatable bags, braking rockets, and shaped surfaces for water impact. It appears feasible to readily evaluate landing-gear systems for internal or external application in hard-surface or water landings by using computational procedures and free-body landing techniques with dynamic models. The systems investigated have shown very interesting energy-dissipation characteristics over a considerable range of landing parameters. Acceptable gear can be developed along lines similar to those presented if stroke requirements and human-tolerance limits are considered.

Urban Expansion: a Geo-Spatial Approach for Temporal Monitoring of Loss of Agricultural Land

NASA Astrophysics Data System (ADS)

Sumari, N. S.; Shao, Z.; Huang, M.; Sanga, C. A.; Van Genderen, J. L.

2017-09-01

This paper presents some preliminary results from research on monitoring the urban growth of Shenzhen in China. Agriculture is still the pillar of national economies in many countries including China. Thus, agriculture contributes to population growth. Population growth follows either exponential or logistic growth models. These models can be examined using a time-series of geospatial data, mainly historical earth observation imagery from satellites such as LANDSAT. Such multitemporal data may provide insights into settlement analysis as well as on population dynamics and hence, quantify the loss of agricultural land. In this study, LANDSAT data of ten dates, at approximately five yearly intervals from 1977 to 2017 were used. The remote sensing techniques used for analysis of data for 40 years were image selection, then followed by geometric and radiometric corrections and mosaicking. Also, classification, remote sensing image fusion, and change detection methods were used. This research extracted the information on the amount, direction, and speed of urbanization, and hence, the number of hectares of agricultural land lost due to urban expansion. Several specific elements were used in the descriptive model of landscape changes and population dynamics of the city of Shenzhen in China. These elements are: i) quantify the urban changes, from a small town (37.000 people in the early 1970's) to the megalopolis of around 20 million habitants today. ii) Examining the rate of urban extension on the loss of agricultural landscape and population growth. iii) The loss of food production was analysed against the economic growth in the region. iv) The aspects of loss of agricultural land, area of built-up urban land, and increase in population are studied quantitatively, by the temporal analysis of earth observation geospatial data. The experimental results from this study show that the proposed method is effective in determining loss of agricultural land in any city due to urbanization. It can be used by town planner and other stakeholders such as land surveyors and agriculture experts to mitigate the mushrooming of unplanned settlements in many town / villages and loss of land for agriculture which might cause problems in food security.

Compositing climate change vulnerability of a Mediterranean region using spatiotemporally dynamic proxies for ecological and socioeconomic impacts and stabilities.

PubMed

Demirkesen, Ali Can; Evrendilek, Fatih

2017-01-01

The study presents a new methodology to quantify spatiotemporal dynamics of climate change vulnerability at a regional scale adopting a new conceptual model of vulnerability as a function of climate change impacts, ecological stability, and socioeconomic stability. Spatiotemporal trends of equally weighted proxy variables for the three vulnerability components were generated to develop a composite climate change vulnerability index (CCVI) for a Mediterranean region of Turkey combining Landsat time series data, digital elevation model (DEM)-derived data, ordinary kriging, and geographical information system. Climate change impact was based on spatiotemporal trends of August land surface temperature (LST) between 1987 and 2016. Ecological stability was based on DEM, slope, aspect, and spatiotemporal trends of normalized difference vegetation index (NDVI), while socioeconomic stability was quantified as a function of spatiotemporal trends of land cover, population density, per capita gross domestic product, and illiteracy. The zones ranked on the five classes of no-to-extreme vulnerability were identified where highly and moderately vulnerable lands covered 0.02% (12 km 2 ) and 11.8% (6374 km 2 ) of the study region, respectively, mostly occurring in the interior central part. The adoption of this composite CCVI approach is expected to lead to spatiotemporally dynamic policy recommendations towards sustainability and tailor preventive and mitigative measures to locally specific characteristics of coupled ecological-socioeconomic systems.

Modeling the transfer of land and water from agricultural to urban uses in the Middle Rio Grande Basin, New Mexico.

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

Jarratt, Janet; Passell, Howard David; Kelly, Susan

2004-11-01

Social and ecological scientists emphasize that effective natural resource management depends in part on understanding the dynamic relationship between the physical and non-physical process associated with resource consumption. In this case, the physical processes include hydrological, climatological and ecological dynamics, and the non-physical process include social, economic and cultural dynamics among humans who do the resource consumption. This project represents a case study aimed at modeling coupled social and physical processes in a single decision support system. In central New Mexico, individual land use decisions over the past five decades have resulted in the gradual transformation of the Middle Riomore » Grande Valley from a primarily rural agricultural landscape to a largely urban one. In the arid southwestern U.S., the aggregate impact of individual decisions about land use is uniquely important to understand, because scarce hydrological resources will likely limit the viability of resulting growth and development trajectories. This decision support tool is intended to help planners in the area look forward in their efforts to create a collectively defined 'desired' social landscape in the Middle Rio Grande. Our research question explored the ways in which socio-cultural values impact decisions regarding that landscape and associated land use. Because of the constraints hydrological resources place on land use, we first assumed that water use, as embodied in water rights, was a reasonable surrogate for land use. We thought that modeling the movement of water rights over time and across water source types (surface and ground) would provide planners with insight into the possibilities for certain types of decisions regarding social landscapes, and the impact those same decisions would have on those landscapes. We found that water rights transfer data in New Mexico is too incomplete and inaccurate to use as the basis for the model. Furthermore, because of its lack of accuracy and completeness, water rights ownership was a poor indicator of water and land usage habits and patterns. We also found that commitment among users in the Middle Rio Grande Valley is to an agricultural lifestyle, not to a community or place. This commitment is conditioned primarily by generational cohort and past experience. If conditions warrant, many would be willing to practice the lifestyle elsewhere. A related finding was that sometimes the pressure to sell was not the putative price of the land, but the taxes on the land. These taxes were, in turn, a function of the level of urbanization of the neighborhood. This urbanization impacted the quality of the agricultural lifestyle. The project also yielded some valuable lessons regarding the model development process. A facilitative and collaborative style (rather than a top-down, directive style) was most productive with the inter-disciplinary , inter-institutional team that worked on the project. This allowed for the emergence of a process model which combined small, discipline- and/or task-specific subgroups with larger, integrating team meetings. The project objective was to develop a model that could be used to run test scenarios in which we explored the potential impact of different policy options. We achieved that objective, although not with the level of success or modeling fidelity which we had hoped for. This report only describes very superficially the results of test scenarios, since more complete analysis of scenarios would require more time and effort. Our greatest obstacle in the successful completion of the project was that required data were sparse, of poor quality, or completely nonexistent. Moreover, we found no similar modeling or research efforts taking place at either the state or local level. This leads to a key finding of this project: that state and local policy decisions regarding land use, development, urbanization, and water resource allocation are being made with minimal data and without the benefit of economic or social policy analysis.« less

Conceptual model for calculation of greenhouse gas emissions from deforestation in the Brazilian Caatinga

NASA Astrophysics Data System (ADS)

Sousa Neto, E. R.; Ometto, J. P.

2012-12-01

The process of removing a forest to open new agricultural lands, which has been very intensive in developing countries like Brazil during the last decades, contributes to about 12% of the global anthropogenic emissions (Le Quéré et al., 2009). Forest cover removal releases carbon and other greenhouse gases like methane (CH4) and nitrous oxide (N2O), as a result of burning trees, followed by gradual decomposition of the forest biomass left on the ground while pasture or crop plantations are being established (Ramankutty et al., 2007). In Brazil, the 2nd Brazilian National Communication to the United Nations Framework Convention on Climate Change (UNFCCC), presents the mean annual net CO2 emissions caused by changes in land use in each Brazilian biome and the first place in the ranking is occupied by the Amazon Rainforest Biome (860,874 Gg), followed by Savannah (302,715 Gg), Atlantic Forest (79,109 Gg), Caatinga (37,628 Gg), Pantanal (16,172 Gg) and Pampa (-102 Gg) (MCT 2010). The estimates of CO2 emissions caused by land use changes in the Brazilian semiarid region (Caatinga) are very limited and scarce, and associated to uncertainties which are directly related to the estimated biomass in different types of vegetation which are spatially distributed within the biome, as well as the correct representation of the dynamics of the deforestation process itself, and the more accurate mapping use and land cover. This project aims to estimate carbon emissions from land use changes in Pernambuco State, Brazil, by using the INPE-EM model. The model will incorporate the temporal dynamics related to the deforestation process, and accounts for the biophysical and socioeconomic heterogeneity of the region in study

Land use, urban, environmental, and cartographic applications, chapter 2, part D

NASA Technical Reports Server (NTRS)

1975-01-01

Microwave data and its use in effective state, regional, and national land use planning are dealt with. Special attention was given to monitoring land use change, especially dynamic components, and the interaction between land use and dynamic features of the environment. Disaster and environmental monitoring are also discussed.

Remote sensing of a dynamic sub-arctic peatland reservoir using optical and synthetic aperture radar data

NASA Astrophysics Data System (ADS)

Larter, Jarod Lee

Stephens Lake, Manitoba is an example of a peatland reservoir that has undergone physical changes related to mineral erosion and peatland disintegration processes since its initial impoundment. In this thesis I focused on the processes of peatland upheaval, transport, and disintegration as the primary drivers of dynamic change within the reservoir. The changes related to these processes are most frequent after initial reservoir impoundment and decline over time. They continue to occur over 35 years after initial flooding. I developed a remote sensing approach that employs both optical and microwave sensors for discriminating land (Le. floating peatlands, forested land, and barren land) from open water within the reservoir. High spatial resolution visible and near-infrared (VNIR) optical data obtained from the QuickBird satellite, and synthetic aperture radar (SAR) microwave data obtained from the RADARSAT-1 satellite were implemented. The approach was facilitated with a Geographic Information System (GIS) based validation map for the extraction of optical and SAR pixel data. Each sensor's extracted data set was first analyzed separately using univariate and multivariate statistical methods to determine the discriminant ability of each sensor. The initial analyses were followed by an integrated sensor approach; the development of an image classification model; and a change detection analysis. Results showed excellent (> 95%) classification accuracy using QuickBird satellite image data. Discrimination and classification of studied land cover classes using SAR image texture data resulted in lower overall classification accuracies (˜ 60%). SAR data classification accuracy improved to > 90% when classifying only land and water, demonstrating SAR's utility as a land and water mapping tool. An integrated sensor data approach showed no considerable improvement over the use of optical satellite image data alone. An image classification model was developed that could be used to map both detailed land cover classes and the land and water interface within the reservoir. Change detection analysis over a seven year period indicated that physical changes related to mineral erosion, peatland upheaval, transport, and disintegration, and operational water level variation continue to take place in the reservoir some 35 years after initial flooding. This thesis demonstrates the ability of optical and SAR satellite image remote sensing data sets to be used in an operational context for the routine discrimination of the land and water boundaries within a dynamic peatland reservoir. Future monitoring programs would benefit most from a complementary image acquisition program in which SAR images, known for their acquisition reliability under cloud cover, are acquired along with optical images given their ability to discriminate land cover classes in greater detail.

Visibility Modeling and Forecasting for Abu Dhabi using Time Series Analysis Method

NASA Astrophysics Data System (ADS)

Eibedingil, I. G.; Abula, B.; Afshari, A.; Temimi, M.

2015-12-01

Land-Atmosphere interactions-their strength, directionality and evolution-are one of the main sources of uncertainty in contemporary climate modeling. A particularly crucial role in sustaining and modulating land-atmosphere interaction is the one of aerosols and dusts. Aerosols are tiny particles suspended in the air ranging from a few nanometers to a few hundred micrometers in diameter. Furthermore, the amount of dust and fog in the atmosphere is an important measure of visibility, which is another dimension of land-atmosphere interactions. Visibility affects all form of traffic, aviation, land and sailing. Being able to predict the change of visibility in the air in advance enables relevant authorities to take necessary actions before the disaster falls. Time Series Analysis (TAS) method is an emerging technique for modeling and forecasting the behavior of land-atmosphere interactions, including visibility. This research assess the dynamics and evolution of visibility around Abu Dhabi International Airport (+24.4320 latitude, +54.6510 longitude, and 27m elevation) using mean daily visibility and mean daily wind speed. TAS has been first used to model and forecast the visibility, and then the Transfer Function Model has been applied, considering the wind speed as an exogenous variable. By considering the Akaike Information Criterion (AIC) and Mean Absolute Percentage Error (MAPE) as a statistical criteria, two forecasting models namely univarite time series model and transfer function model, were developed to forecast the visibility around Abu Dhabi International Airport for three weeks. Transfer function model improved the MAPE of the forecast significantly.

Soil Water Balance and Vegetation Dynamics in two Contrasting Water-limited Mediterranean Ecosystems on Sardinia, Italy

NASA Astrophysics Data System (ADS)

Montaldo, N.; Albertson, J. D.; Corona, R.

2011-12-01

Water limited conditions strongly impacts soil and vegetation dynamics in Mediterranean regions, which are commonly heterogeneous ecosystems, characterized by inter-annual rainfall variability, topography variability and contrasting plant functional types (PFTs) competing for water use. Mediterranean regions are characterized by two main ecosystems, grassland and woodland, which for both natural and anthropogenic causes can grow in soils with different characteristics, highly impacting water resources. Water resources and forestal planning need a deep understanding of the dynamics between PFTs, soil and atmosphere and their impacts on water and CO2 distributions of these two main ecosystems. The first step is the monitoring of land surface fluxes, soil moisture, and vegetation dynamics of the two contrasting ecosystems. Moreover, due to the large percentage of soils with low depth (< 50 cm), and due to the quick hydrologic answer to atmospheric forcing in these soils, there is also the need to understand the impact of the soil depth in the vegetation dynamics, and make measurements in these types of soils. Sardinia island is a very interesting and representative region of Mediterranean ecosystems. It is low urbanized, and is not irrigated, except some plan areas close to the main cities where main agricultural activities are concentrated. The case study sites are within the Flumendosa river basin on Sardinia. Two sites, both in the Flumendosa river and with similar height a.s.l., are investigated. The distance between the sites is around 4 km but the first is a typically grass site located on an alluvial plan valley with a soil depth more than 2m, while the second site is a patchy mixture of Mediterranean vegetation types Oaks, creepers of the wild olive trees and C3 herbaceous species and the soil thickness varies from 15-40 cm, bounded from below by a rocky layer of basalt, partially fractured. In both sites land-surface fluxes and CO2 fluxes are estimated by eddy correlation technique based micrometeorological towers. Soil moisture profiles were also continuously estimated using water content reflectometers and gravimetric method, and periodically leaf area index PFTs are estimated during the Spring-Summer 2005. The following objectives are addressed:1) pointing out the dynamics of land surface fluxes, soil moisture, CO2 and vegetation cover for two contrasting water-limited ecosystems; 2) assess the impact of the soil depth and type on the CO2 and water balance dynamics. For reaching the objectives an ecohydrologic model is also successfully used and applied to the case studies. It couples a vegetation dynamic model, which computes the change in biomass over time for the PFTs, and a 3-component (bare soil, grass and woody vegetation) land surface model.

Dynamic analysis of lunar lander during soft landing using explicit finite element method

NASA Astrophysics Data System (ADS)

Zheng, Guang; Nie, Hong; Chen, Jinbao; Chen, Chuanzhi; Lee, Heow Pueh

2018-07-01

In this paper, the soft-landing analysis of a lunar lander spacecraft under three loading case was carried out in ABAQUS, using the Explicit Finite Element method. To ensure the simulation result's accuracy and reliability, the energy and mass balance criteria of the model was presented along with the theory and calculation method, and the results were benchmarked with other software (LS-DYNA) to get a validated model. The results from three loading case showed that the energy and mass of the models were conserved during soft landing, which satisfies the energy and mass balance criteria. The overloading response, structure steady state, and the crushing stroke of this lunar lander all met the design requirements of the lunar lander. The buffer energy-absorbing properties in this model have a good energy-absorbing capability, in which up to 84% of the initial energy could be dissipated. The design parameters of the model could guide the design of future manned landers or larger lunar landers.

Understanding the Impacts of Climate Change and Land Use Dynamics Using a Fully Coupled Hydrologic Feedback Model between Surface and Subsurface Systems

NASA Astrophysics Data System (ADS)

Park, C.; Lee, J.; Koo, M.

2011-12-01

Climate is the most critical driving force of the hydrologic system of the Earth. Since the industrial revolution, the impacts of anthropogenic activities to the Earth environment have been expanded and accelerated. Especially, the global emission of carbon dioxide into the atmosphere is known to have significantly increased temperature and affected the hydrologic system. Many hydrologists have contributed to the studies regarding the climate change on the hydrologic system since the Intergovernmental Panel on Climate Change (IPCC) was created in 1988. Among many components in the hydrologic system groundwater and its response to the climate change and anthropogenic activities are not fully understood due to the complexity of subsurface conditions between the surface and the groundwater table. A new spatio-temporal hydrologic model has been developed to estimate the impacts of climate change and land use dynamics on the groundwater. The model consists of two sub-models: a surface model and a subsurface model. The surface model involves three surface processes: interception, runoff, and evapotranspiration, and the subsurface model does also three subsurface processes: soil moisture balance, recharge, and groundwater flow. The surface model requires various input data including land use, soil types, vegetation types, topographical elevations, and meteorological data. The surface model simulates daily hydrological processes for rainfall interception, surface runoff varied by land use change and crop growth, and evapotranspiration controlled by soil moisture balance. The daily soil moisture balance is a key element to link two sub-models as it calculates infiltration and groundwater recharge by considering a time delay routing through a vadose zone down to the groundwater table. MODFLOW is adopted to simulate groundwater flow and interaction with surface water components as well. The model is technically flexible to add new model or modify existing model as it is developed with an object-oriented language - Python. The model also can easily be localized by simple modification of soil and crop properties. The actual application of the model after calibration was successful and results showed reliable water balance and interaction between the surface and subsurface hydrologic systems.

Modeling surface energy fluxes from a patchwork of fields with different soils and crops

NASA Astrophysics Data System (ADS)

Klein, Christian; Thieme, Christoph; Heinlein, Florian; Priesack, Eckart

2017-04-01

Agroecosystems are a dominant terrestrial land-use on planet earth and cover about 36% of the ice-free surface (12% pasture, 26% agriculture) [Foley2011]. Within this land use type, management practices vary strongly due to climate, cultural preferences, degree of industrialization, soil properties, crop rotations, field sizes, degree of land use sustainability, water availability, sowing and harvest dates, tillage, etc. These management practices influence abiotic environmental factors like water flow and heat transport within the ecosystem leading to changes of land surface fluxes. The relevance of vegetation (e.g. crops), ground cover, and soil properties to the moisture and energy exchanges between the land surface and the atmosphere is well known [McPherson 2007], but the impact of vegetation growth dynamics on energy fluxes is only partly understood [Gayler et al. 2014]. Thus, the structure of turbulence and the albedo evolve during the cropping period and large variations of heat can be measured on the field scale [Aubinet2012]. One issue of local distributed mixture of different land use is the measurement process which makes it challenging to evaluate simulations. Unfortunately, for meteorological flux-measurements like the Flux-Gradient or the Eddy Covariance (EC) method, comparability with simulations only exists in the ideal case, where fields have to be completely uniform in land use and flat within the reach of the footprint. Then a model with one specific land use would have the same underlying source area as the measurement. An elegant method to avoid the shortcoming of grid cell resolution is the so called mixed approach, which was recently implemented into the ecosystem model framework Expert-N [Biernath et al. 2013]. The aim of this study was to analyze the impact of the characteristics of five managed field plots, planted with winter wheat, potato and maize on the near surface soil moistures and on the near surface energy flux exchanges of the soil-plant-atmosphere interface. The simulated energy fluxes were compared with eddy flux tower measurements between the respective fields at the research farm Scheyern, North-West of Munich, Germany. These simulations were done by coupling the ecosystem model Expert-N to an analytical footprint model [Mauder & Foken 2011] . The coupled model system has the ability to calculate the mixing ratio of the surface energy fluxes at the flux tower position. The approach accounts for the temporarily and spatially changing contributions of the patchwork of environmental land surface conditions (land use, management, soil properties) which influence the energy flux tower measurements due to the footprint dynamics. The statistical evaluation between simulation and measurements showed that the mixed approach improved the comparability in most cases. Furthermore, the management impact on single patches can be clearly detected, both in the measurements and the simulation. We conclude that reasonable simulations of energy and matter fluxes can be obtained if the heterogeneity of the land surfaces is taken into account.

West Africa land use and land cover time series

USGS Publications Warehouse

Cotillon, Suzanne E.

2017-02-16

Started in 1999, the West Africa Land Use Dynamics project represents an effort to map land use and land cover, characterize the trends in time and space, and understand their effects on the environment across West Africa. The outcome of the West Africa Land Use Dynamics project is the production of a three-time period (1975, 2000, and 2013) land use and land cover dataset for the Sub-Saharan region of West Africa, including the Cabo Verde archipelago. The West Africa Land Use Land Cover Time Series dataset offers a unique basis for characterizing and analyzing land changes across the region, systematically and at an unprecedented level of detail.

Impact of land use change on the land atmosphere carbon flux of South and South East Asia: A Synthesis of Dynamic Vegetation Model Results

NASA Astrophysics Data System (ADS)

Cervarich, M.; Shu, S.; Jain, A. K.; Poulter, B.; Stocker, B.; Arneth, A.; Viovy, N.; Kato, E.; Wiltshire, A.; Koven, C.; Sitch, S.; Zeng, N.; Friedlingstein, P.

2015-12-01

Understanding our present day carbon cycle and possible solutions to recent increases in atmospheric carbon dioxide is dependent upon quantifying the terrestrial carbon budget. Currently, global land cover and land use change is estimated to emit 0.9 PgC yr-1 compared to emissions due to fossil fuel combustion and cement production of 8.4 PgC yr-1. South and Southeast Asia (India, Nepal, Bhutan, Bangladesh, Burma, Thailand, Laos, Vietnam, Cambodia, Malaysia, Philippines, Indonesia, Pakistan, Myanmar, and Singapore) is a region of rapid land cover and land use change due to the continuous development of agriculture, deforestation, reforestation, afforestation, and the increased demand of land for people to live. In this study, we synthesize outputs of nine models participated in Global Carbon Budget Project to identify the carbon budget of South and southeast Asia, diagnose the contribution of land cover and land use change to carbon emissions and assess areas of uncertainty in the suite of models. Uncertainty is determined using the standard deviation and the coefficient of variation of net ecosystem exchange and its component parts. Results show the region's terrestrial biosphere was a source of carbon emissions from the 1980 to the early 1990s. During the same time period, land cover and land use change increasingly contributed to carbon emission. In the most recent two decades, the region became a carbon sink since emission due to land cover land use changes. Spatially, the greatest total emissions occurred in the tropical forest of Southeast Asia. Additionally, this is the subregion with the greatest uncertainty and greatest biomass. Model uncertainty is shown to be proportional to total biomass. The atmospheric impacts of ENSO are shown to suppress the net biosphere productivity in South and Southeast Asia leading to years of increased carbon emissions.

Transient dynamics of terrestrial carbon storage: Mathematical foundation and numeric examples

DOE PAGES

Luo, Yiqi; Shi, Zheng; Lu, Xingjie; ...

2016-09-16

Terrestrial ecosystems absorb roughly 30% of anthropogenic CO 2 emissions since preindustrial era, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling, experimental, and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under climate change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production,more » NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Furthermore, this and our other studies have demonstrated that one matrix equation can exactly replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. Moreover, the emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. We also propose that the C storage potential be the targeted variable for research, market trading, and government negotiation for C credits.« less

Transient dynamics of terrestrial carbon storage: Mathematical foundation and numeric examples

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

Luo, Yiqi; Shi, Zheng; Lu, Xingjie

Terrestrial ecosystems absorb roughly 30% of anthropogenic CO 2 emissions since preindustrial era, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling, experimental, and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under climate change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production,more » NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Furthermore, this and our other studies have demonstrated that one matrix equation can exactly replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. Moreover, the emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. We also propose that the C storage potential be the targeted variable for research, market trading, and government negotiation for C credits.« less

Modeling temporal and spatial variability of traffic-related air pollution: Hourly land use regression models for black carbon

NASA Astrophysics Data System (ADS)

Dons, Evi; Van Poppel, Martine; Kochan, Bruno; Wets, Geert; Int Panis, Luc

2013-08-01

Land use regression (LUR) modeling is a statistical technique used to determine exposure to air pollutants in epidemiological studies. Time-activity diaries can be combined with LUR models, enabling detailed exposure estimation and limiting exposure misclassification, both in shorter and longer time lags. In this study, the traffic related air pollutant black carbon was measured with μ-aethalometers on a 5-min time base at 63 locations in Flanders, Belgium. The measurements show that hourly concentrations vary between different locations, but also over the day. Furthermore the diurnal pattern is different for street and background locations. This suggests that annual LUR models are not sufficient to capture all the variation. Hourly LUR models for black carbon are developed using different strategies: by means of dummy variables, with dynamic dependent variables and/or with dynamic and static independent variables. The LUR model with 48 dummies (weekday hours and weekend hours) performs not as good as the annual model (explained variance of 0.44 compared to 0.77 in the annual model). The dataset with hourly concentrations of black carbon can be used to recalibrate the annual model, resulting in many of the original explaining variables losing their statistical significance, and certain variables having the wrong direction of effect. Building new independent hourly models, with static or dynamic covariates, is proposed as the best solution to solve these issues. R2 values for hourly LUR models are mostly smaller than the R2 of the annual model, ranging from 0.07 to 0.8. Between 6 a.m. and 10 p.m. on weekdays the R2 approximates the annual model R2. Even though models of consecutive hours are developed independently, similar variables turn out to be significant. Using dynamic covariates instead of static covariates, i.e. hourly traffic intensities and hourly population densities, did not significantly improve the models' performance.

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.

Land-use change and infectious disease in West Africa

NASA Astrophysics Data System (ADS)

Thomson, M. C.; Ericksen, P. J.; Mohamed, A. Ben; Connor, S. J.

Land-use change has been associated with changes in the dynamics of infectious disease in West Africa. Here we describe the complex interactions of land-use change with three diseases (both vector- and non-vector-borne) of considerable public health significance in this region, namely, malaria and irrigation; epidemic meningitis and land degradation; onchocerciasis and deforestation. We highlight the confounding effect of climate variability, which acts as a driver of both land-use change and human health. We conclude, as have others, that the scale of observation always matters, and complex and dynamic feedbacks among social-ecological systems are not easily teased apart. We suggest that in order to establish the causal chain of interactions between land-use change and human health outcomes two approaches are necessary. The first is to have a thorough understanding of the aetiology of disease and the specific mechanisms by which land-use and climate variability affect the transmission of pathogens. This is achieved by focused, detailed studies encompassing a wide range of potential drivers, which are inevitably small scale and often cover short time periods. The second consists of large-scale studies of statistical associations between transmission indices or health outcomes and environmental variables stratified by known ecological or socio-economic confounders, and sufficient in size to overcome local biases in results. Such research activities need to be designed to inform each other if we are to develop predictive models for monitoring these diseases and to develop integrated programs for human health and sustainable land use.

Vegetation and Carbon Cycle Dynamics in the High-Resolution Transient Holocene Simulations Using the MPI Earth System Model

NASA Astrophysics Data System (ADS)

Brovkin, V.; Lorenz, S.; Raddatz, T.; Claussen, M.; Dallmeyer, A.

2017-12-01

One of the interesting periods to investigate a climatic role of terrestrial biosphere is the Holocene, when, despite of the relatively steady global climate, the atmospheric CO2 grew by about 20 ppm from 7 kyr BP to pre-industrial. We use a new setup of the Max Planck Institute Earth System Model MPI-ESM1 consisting of the latest version of the atmospheric model ECHAM6, including the land surface model JSBACH3 with carbon cycle and vegetation dynamics, coupled to the ocean circulation model MPI-OM, which includes the HAMOCC model of ocean biogeochemistry. The model has been run for several simulations over the Holocene period of the last 8000 years under the forcing data sets of orbital insolation, atmospheric greenhouse gases, volcanic aerosols, solar irradiance and stratospheric ozone, as well as land-use changes. In response to this forcing, the land carbon storage increased by about 60 PgC between 8 and 4 kyr BP, stayed relatively constant until 2 kyr BP, and decreased by about 90 PgC by 1850 AD due to land use changes. At 8 kyr BP, vegetation cover was much denser in Africa, mainly due to increased rainfall in response to the orbital forcing. Boreal forests moved northward in both, North America and Eurasia. The boreal forest expansion in North America is much less pronounced than in Eurasia. Simulated physical ocean fields, including surface temperatures and meridional overturning, do not change substantially in the Holocene. Carbonate ion concentration in deep ocean decreases in both, prescribed and interactive CO2simulations. Comparison with available proxies for terrestrial vegetation and for the ocean carbonate chemistry will be presented. Vegetation and soil carbon changes significantly affected atmospheric CO2 during the periods of strong volcanic eruptions. In response to the eruption-caused cooling, the land initially stores more carbon as respiration decreases, but then it releases even more carbon die to productivity decrease. This decadal-scale variability helps to quantify the vegetation and land carbon feedbacks during the past periods when the temporal resolution of the ice-core CO2 record is not sufficient to capture fast CO2 variations. From a set of Holocene simulations with prescribed or interactive atmospheric CO2, we get estimates of climate-carbon feedback useful for future climate studies.

The new GFDL global atmosphere and land model AM2-LM2: Evaluation with prescribed SST simulations

USGS Publications Warehouse

Anderson, J.L.; Balaji, V.; Broccoli, A.J.; Cooke, W.F.; Delworth, T.L.; Dixon, K.W.; Donner, L.J.; Dunne, K.A.; Freidenreich, S.M.; Garner, S.T.; Gudgel, R.G.; Gordon, C.T.; Held, I.M.; Hemler, R.S.; Horowitz, L.W.; Klein, S.A.; Knutson, T.R.; Kushner, P.J.; Langenhost, A.R.; Lau, N.-C.; Liang, Z.; Malyshev, S.L.; Milly, P.C.D.; Nath, M.J.; Ploshay, J.J.; Ramaswamy, V.; Schwarzkopf, M.D.; Shevliakova, E.; Sirutis, J.J.; Soden, B.J.; Stern, W.F.; Thompson, L.A.; Wilson, R.J.; Wittenberg, A.T.; Wyman, B.L.

2004-01-01

The configuration and performance of a new global atmosphere and land model for climate research developed at the Geophysical Fluid Dynamics Laboratory (GFDL) are presented. The atmosphere model, known as AM2, includes a new gridpoint dynamical core, a prognostic cloud scheme, and a multispecies aerosol climatology, as well as components from previous models used at GFDL. The land model, known as LM2, includes soil sensible and latent heat storage, groundwater storage, and stomatal resistance. The performance of the coupled model AM2-LM2 is evaluated with a series of prescribed sea surface temperature (SST) simulations. Particular focus is given to the model's climatology and the characteristics of interannual variability related to El Nin??o-Southern Oscillation (ENSO). One AM2-LM2 integration was perfor med according to the prescriptions of the second Atmospheric Model Intercomparison Project (AMIP II) and data were submitted to the Program for Climate Model Diagnosis and Intercomparison (PCMDI). Particular strengths of AM2-LM2, as judged by comparison to other models participating in AMIP II, include its circulation and distributions of precipitation. Prominent problems of AM2-LM2 include a cold bias to surface and tropospheric temperatures, weak tropical cyclone activity, and weak tropical intraseasonal activity associated with the Madden-Julian oscillation. An ensemble of 10 AM2-LM 2 integrations with observed SSTs for the second half of the twentieth century permits a statistically reliable assessment of the model's response to ENSO. In general, AM2-LM2 produces a realistic simulation of the anomalies in tropical precipitation and extratropical circulation that are associated with ENSO. ?? 2004 American Meteorological Society.

LPJmL4 - a dynamic global vegetation model with managed land - Part 1: Model description

NASA Astrophysics Data System (ADS)

Schaphoff, Sibyll; von Bloh, Werner; Rammig, Anja; Thonicke, Kirsten; Biemans, Hester; Forkel, Matthias; Gerten, Dieter; Heinke, Jens; Jägermeyr, Jonas; Knauer, Jürgen; Langerwisch, Fanny; Lucht, Wolfgang; Müller, Christoph; Rolinski, Susanne; Waha, Katharina

2018-04-01

This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates - internally consistently - the growth and productivity of both natural and agricultural vegetation as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial biosphere as increasingly shaped by human activities such as climate change and land use change. Here we describe the core model structure, including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand, and improved representation of crop types. We summarize and discuss LPJmL model applications dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL, we hope to stimulate the application and further development of LPJmL4 across scientific communities in support of major activities such as the IPCC and SDG process.

The Joint UK Land Environment Simulator (JULES), Model description - Part 2: Carbon fluxes and vegetation

NASA Astrophysics Data System (ADS)

Clark, D. B.; Mercado, L. M.; Sitch, S.; Jones, C. D.; Gedney, N.; Best, M. J.; Pryor, M.; Rooney, G. G.; Essery, R. L. H.; Blyth, E.; Boucher, O.; Harding, R. J.; Cox, P. M.

2011-03-01

The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Past studies with JULES have demonstrated the important role of the land surface in the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of separately changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. There was a need to consolidate these and other advances into a single model code so as to be able to study interactions in a consistent manner. This paper describes the consolidation of these advances into the modelling of carbon fluxes and stores, in the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.

Ditching Investigation of a 1/12-Scale Model of the Douglas F4D-1 Airplane, TED No. NACA DE 384

NASA Technical Reports Server (NTRS)

Windham, John O.

1956-01-01

A ditching investigation was made of a l/l2-scale dynamically similar model of the Douglas F4D-1 airplane to study its behavior when ditched. The model was landed in calm water at the Langley tank no. 2 monorail. Various landing attitudes, speeds, and configurations were investigated. The behavior of the model was determined from visual observations, acceleration records, and motion-picture records of the ditchings. Data are presented in tables, sequence photographs, time-history acceleration curves, and attitude curves. From the results of the investigation, it was concluded that the airplane should be ditched at the lowest speed and highest attitude consistent with adequate control (near 22 deg) with landing gear retracted. In a calm-water ditching under these conditions the airplane will probably nose in slightly, then make a fairly smooth run. The fuselage bottom will sustain appreciable damage so that rapid flooding and short flotation time are likely. Maximum longitudinal deceleration will be about 4g and maximum normal acceleration will be about 6g in a landing run of about 420 feet, In a calm-water ditching under similar conditions with the landing gear extended, the airplane will probably dive. Maximum longitudinal decelerations will be about 5-1/2g and maximum normal accelerations will be about 3-1/2g in a landing run of about 170 feet.

Using Poaching Levels and Elephant Distribution to Assess the Conservation Efficacy of Private, Communal and Government Land in Northern Kenya

PubMed Central

Ihwagi, Festus W.; Wang, Tiejun; Wittemyer, George; Skidmore, Andrew K.; Toxopeus, Albertus G.; Ngene, Shadrack; King, Juliet; Worden, Jeffrey; Omondi, Patrick; Douglas-Hamilton, Iain

2015-01-01

Efforts to curb elephant poaching have focused on reducing demand, confiscating ivory and boosting security patrols in elephant range. Where land is under multiple uses and ownership, determining the local poaching dynamics is important for identifying successful conservation models. Using 2,403 verified elephant, Loxodonta africana, mortality records collected from 2002 to 2012 and the results of aerial total counts of elephants conducted in 2002, 2008 and 2012 for the Laikipia-Samburu ecosystem of northern Kenya, we sought to determine the influence of land ownership and use on diurnal elephant distribution and on poaching levels. We show that the annual proportions of illegally killed (i.e., poached) elephants increased over the 11 years of the study, peaking at 70% of all recorded deaths in 2012. The type of land use was more strongly related to levels of poaching than was the type of ownership. Private ranches, comprising only 13% of land area, hosted almost half of the elephant population and had significantly lower levels of poaching than other land use types except for the officially designated national reserves (covering only 1.6% of elephant range in the ecosystem). Communal grazing lands hosted significantly fewer elephants than expected, but community areas set aside for wildlife demonstrated significantly higher numbers of elephants and lower illegal killing levels relative to non-designated community lands. While private lands had lower illegal killing levels than community conservancies, the success of the latter relative to other community-held lands shows the importance of this model of land use for conservation. This work highlights the relationship between illegal killing and various land ownership and use models, which can help focus anti-poaching activities. PMID:26407001

Optimal land use management for soil erosion control by using an interval-parameter fuzzy two-stage stochastic programming approach.

PubMed

Han, Jing-Cheng; Huang, Guo-He; Zhang, Hua; Li, Zhong

2013-09-01

Soil erosion is one of the most serious environmental and public health problems, and such land degradation can be effectively mitigated through performing land use transitions across a watershed. Optimal land use management can thus provide a way to reduce soil erosion while achieving the maximum net benefit. However, optimized land use allocation schemes are not always successful since uncertainties pertaining to soil erosion control are not well presented. This study applied an interval-parameter fuzzy two-stage stochastic programming approach to generate optimal land use planning strategies for soil erosion control based on an inexact optimization framework, in which various uncertainties were reflected. The modeling approach can incorporate predefined soil erosion control policies, and address inherent system uncertainties expressed as discrete intervals, fuzzy sets, and probability distributions. The developed model was demonstrated through a case study in the Xiangxi River watershed, China's Three Gorges Reservoir region. Land use transformations were employed as decision variables, and based on these, the land use change dynamics were yielded for a 15-year planning horizon. Finally, the maximum net economic benefit with an interval value of [1.197, 6.311] × 10(9) $ was obtained as well as corresponding land use allocations in the three planning periods. Also, the resulting soil erosion amount was found to be decreased and controlled at a tolerable level over the watershed. Thus, results confirm that the developed model is a useful tool for implementing land use management as not only does it allow local decision makers to optimize land use allocation, but can also help to answer how to accomplish land use changes.