The challenges associated with applying global models in heterogeneous landscapes: A case study using MOD17 GPP estimates in Hawaii

NASA Astrophysics Data System (ADS)

Kimball, H.; Selmants, P. C.; Running, S. W.; Moreno, A.; Giardina, C. P.

2016-12-01

In this study we evaluate the influence of spatial data product accuracy and resolution on the application of global models for smaller scale heterogeneous landscapes. In particular, we assess the influence of locally specific land cover and high-resolution climate data products on estimates of Gross Primary Production (GPP) for the Hawaiian Islands using the MOD17 model. The MOD17 GPP algorithm uses a measure of the fraction of absorbed photosynthetically active radiation from the National Aeronautics and Space Administration's Earth Observation System. This direct measurement is combined with global land cover (500-m resolution) and climate models ( 1/2-degree resolution) to estimate GPP. We first compared the alignment between the global land cover model used in MOD17 with a Hawaii specific land cover data product. We found that there was a 51.6% overall agreement between the two land cover products. We then compared four MOD17 GPP models: A global model that used the global land cover and low-resolution global climate data products, a model produced using the Hawaii specific land cover and low-resolution global climate data products, a model with global land cover and high-resolution climate data products, and finally, a model using both Hawaii specific land cover and high-resolution climate data products. We found that including either the Hawaii specific land cover or the high-resolution Hawaii climate data products with MOD17 reduced overall estimates of GPP by 8%. When both were used, GPP estimates were reduced by 16%. The reduction associated with land cover is explained by a reduction of the total area designated as evergreen broad leaf forest and an increase in the area designated as barren or sparsely vegetated in the Hawaii land cover product as compared to the global product. The climate based reduction is explained primarily by the spatial resolution and distribution of solar radiation in the Hawaiian Islands. This study highlights the importance of accuracy and resolution when applying global models to highly variable landscapes and provides an estimate of the influence of land cover and climate data products on estimates of GPP using MOD17.

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.

New land surface digital elevation model covers the Earth

USGS Publications Warehouse

Gesch, Dean B.; Verdin, Kristine L.; Greenlee, Susan K.

1999-01-01

Land surface elevation around the world is reaching new heights—as far as its description and measurement goes. A new global digital elevation model (DEM) is being cited as a significant improvement in the quality of topographic data available for Earth science studies.Land surface elevation is one of the Earth's most fundamental geophysical properties, but the accuracy and detail with which it has been measured and described globally have been insufficient for many large-area studies. The new model, developed at the U.S. Geological Survey's (USGS) EROS Data Center (EDC), has changed all that.

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.

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).

OPAL Netlogo Land Condition Model

DTIC Science & Technology

2014-08-15

ER D C/ CE RL T R- 14 -1 2 Optimal Allocation of Land for Training and Non-training Uses ( OPAL ) OPAL Netlogo Land Condition Model...Fulton, Natalie Myers, Scott Tweddale, Dick Gebhart, Ryan Busby, Anne Dain-Owens, and Heidi Howard August 2014 OPAL team measuring above and...online library at http://acwc.sdp.sirsi.net/client/default. Optimal Allocation of Land for Training and Non-training Uses ( OPAL ) ERDC/CERL TR-14-12

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.

Exploring dust emission responses to land cover change using an ecological land classification

NASA Astrophysics Data System (ADS)

Galloza, Magda S.; Webb, Nicholas P.; Bleiweiss, Max P.; Winters, Craig; Herrick, Jeffrey E.; Ayers, Eldon

2018-06-01

Despite efforts to quantify the impacts of land cover change on wind erosion, assessment uncertainty remains large. We address this uncertainty by evaluating the application of ecological site concepts and state-and-transition models (STMs) for detecting and quantitatively describing the impacts of land cover change on wind erosion. We apply a dust emission model over a rangeland study area in the northern Chihuahuan Desert, New Mexico, USA, and evaluate spatiotemporal patterns of modelled horizontal sediment mass flux and dust emission in the context of ecological sites and their vegetation states; representing a diversity of land cover types. Our results demonstrate how the impacts of land cover change on dust emission can be quantified, compared across land cover classes, and interpreted in the context of an ecological model that encapsulates land management intensity and change. Results also reveal the importance of established weaknesses in the dust model soil characterisation and drag partition scheme, which appeared generally insensitive to the impacts of land cover change. New models that address these weaknesses, coupled with ecological site concepts and field measurements across land cover types, could significantly reduce assessment uncertainties and provide opportunities for identifying land management options.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Research Advances on Radiation Transfer Modeling and Inversion for Multi-scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.; Li, J.; Du, Y.; Wen, J.; Zhong, B.; Wang, K.

2011-12-01

As the remote sensing data accumulating, it is a challenge and significant issue how to generate high accurate and consistent land surface parameter product from the multi source remote observation and the radiation transfer modeling and inversion methodology are the theoretical bases. In this paper, recent research advances and unresolved issues are presented. At first, after a general overview, recent research advances on multi-scale remote sensing radiation transfer modeling are presented, including leaf spectrum model, vegetation canopy BRDF models, directional thermal infrared emission models, rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed, taking the land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is suggested and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China are introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

Modelling Nitrogen Oxides in Los Angeles Using a Hybrid Dispersion/Land Use Regression Model

NASA Astrophysics Data System (ADS)

Wilton, Darren C.

The goal of this dissertation is to develop models capable of predicting long term annual average NOx concentrations in urban areas. Predictions from simple meteorological dispersion models and seasonal proxies for NO2 oxidation were included as covariates in a land use regression (LUR) model for NOx in Los Angeles, CA. The NO x measurements were obtained from a comprehensive measurement campaign that is part of the Multi-Ethnic Study of Atherosclerosis Air Pollution Study (MESA Air). Simple land use regression models were initially developed using a suite of GIS-derived land use variables developed from various buffer sizes (R²=0.15). Caline3, a simple steady-state Gaussian line source model, was initially incorporated into the land-use regression framework. The addition of this spatio-temporally varying Caline3 covariate improved the simple LUR model predictions. The extent of improvement was much more pronounced for models based solely on the summer measurements (simple LUR: R²=0.45; Caline3/LUR: R²=0.70), than it was for models based on all seasons (R²=0.20). We then used a Lagrangian dispersion model to convert static land use covariates for population density, commercial/industrial area into spatially and temporally varying covariates. The inclusion of these covariates resulted in significant improvement in model prediction (R²=0.57). In addition to the dispersion model covariates described above, a two-week average value of daily peak-hour ozone was included as a surrogate of the oxidation of NO2 during the different sampling periods. This additional covariate further improved overall model performance for all models. The best model by 10-fold cross validation (R²=0.73) contained the Caline3 prediction, a static covariate for length of A3 roads within 50 meters, the Calpuff-adjusted covariates derived from both population density and industrial/commercial land area, and the ozone covariate. This model was tested against annual average NOx concentrations from an independent data set from the EPA's Air Quality System (AQS) and MESA Air fixed site monitors, and performed very well (R²=0.82).

Nitrate removal in stream ecosystems measured by 15N addition experiments: Total uptake

USGS Publications Warehouse

Hall, R.O.; Tank, J.L.; Sobota, D.J.; Mulholland, P.J.; O'Brien, J. M.; Dodds, W.K.; Webster, J.R.; Valett, H.M.; Poole, G.C.; Peterson, B.J.; Meyer, J.L.; McDowell, W.H.; Johnson, S.L.; Hamilton, S.K.; Grimm, N. B.; Gregory, S.V.; Dahm, Clifford N.; Cooper, L.W.; Ashkenas, L.R.; Thomas, S.M.; Sheibley, R.W.; Potter, J.D.; Niederlehner, B.R.; Johnson, L.T.; Helton, A.M.; Crenshaw, C.M.; Burgin, A.J.; Bernot, M.J.; Beaulieu, J.J.; Arangob, C.P.

2009-01-01

We measured uptake length of 15NO-3 in 72 streams in eight regions across the United States and Puerto Rico to develop quantitative predictive models on controls of NO-3 uptake length. As part of the Lotic Intersite Nitrogen eXperiment II project, we chose nine streams in each region corresponding to natural (reference), suburban-urban, and agricultural land uses. Study streams spanned a range of human land use to maximize variation in NO-3 concentration, geomorphology, and metabolism. We tested a causal model predicting controls on NO-3 uptake length using structural equation modeling. The model included concomitant measurements of ecosystem metabolism, hydraulic parameters, and nitrogen concentration. We compared this structural equation model to multiple regression models which included additional biotic, catchment, and riparian variables. The structural equation model explained 79% of the variation in log uptake length (S Wtot). Uptake length increased with specific discharge (Q/w) and increasing NO-3 concentrations, showing a loss in removal efficiency in streams with high NO-3 concentration. Uptake lengths shortened with increasing gross primary production, suggesting autotrophic assimilation dominated NO-3 removal. The fraction of catchment area as agriculture and suburban-urban land use weakly predicted NO-3 uptake in bivariate regression, and did improve prediction in a set of multiple regression models. Adding land use to the structural equation model showed that land use indirectly affected NO-3 uptake lengths via directly increasing both gross primary production and NO-3 concentration. Gross primary production shortened SWtot, while increasing NO-3 lengthened SWtot resulting in no net effect of land use on NO- 3 removal. ?? 2009.

Research Advances on Radiation Transfer Modeling and Inversion for Multi-Scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.

2011-09-01

At first, research advances on radiation transfer modeling on multi-scale remote sensing data are presented: after a general overview of remote sensing radiation transfer modeling, several recent research advances are presented, including leaf spectrum model (dPROS-PECT), vegetation canopy BRDF models, directional thermal infrared emission models(TRGM, SLEC), rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed. The land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation etc. are taken as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is designed and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China will be introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

Implication of remotely sensed data to incorporate land cover effect into a linear reservoir-based rainfall-runoff model

USDA-ARS?s Scientific Manuscript database

This study investigates the effect of land use on the Geomorphological Cascade of unequal Linear Reservoirs (GCUR) model. We use the Normalized Difference Vegetation Index (NDVI) derived from remotely sensed data as a measure of land use. Our approach has two important aspects: (i) it considers the ...

Development and Evaluation of Land-Use Regression Models Using Modeled Air Quality Concentrations

EPA Science Inventory

Abstract Land-use regression (LUR) models have emerged as a preferred methodology for estimating individual exposure to ambient air pollution in epidemiologic studies in absence of subject-specific measurements. Although there is a growing literature focused on LUR evaluation, fu...

A modelling approach for the assessment of the effects of Common Agricultural Policy measures on farmland biodiversity in the EU27.

PubMed

Overmars, Koen P; Helming, John; van Zeijts, Henk; Jansson, Torbjörn; Terluin, Ida

2013-09-15

In this paper we describe a methodology to model the impacts of policy measures within the Common Agricultural Policy (CAP) on farm production, income and prices, and on farmland biodiversity. Two stylised scenarios are used to illustrate how the method works. The effects of CAP measures, such as subsidies and regulations, are calculated and translated into changes in land use and land-use intensity. These factors are then used to model biodiversity with a species-based indicator on a 1 km scale in the EU27. The Common Agricultural Policy Regionalised Impact Modelling System (CAPRI) is used to conduct the economic analysis and Dyna-CLUE (Conversion of Land Use and its Effects) is used to model land use changes. An indicator that expresses the relative species richness was used as the indicator for biodiversity in agricultural areas. The methodology is illustrated with a baseline scenario and two scenarios that include a specific policy. The strength of the methodology is that impacts of economic policy instruments can be linked to changes in agricultural production, prices and incomes, on the one hand, and to biodiversity effects, on the other - with land use and land-use intensity as the connecting drivers. The method provides an overall assessment, but for detailed impact assessment at landscape, farm or field level, additional analysis would be required. Copyright © 2013 Elsevier Ltd. All rights reserved.

NASA High-Speed 2D Photogrammetric Measurement System

NASA Technical Reports Server (NTRS)

Dismond, Harriett R.

2012-01-01

The object of this report is to provide users of the NASA high-speed 2D photogrammetric measurement system with procedures required to obtain drop-model trajectory and impact data for full-scale and sub-scale models. This guide focuses on use of the system for vertical drop testing at the NASA Langley Landing and Impact Research (LandIR) Facility.

Sensitivity of selected landscape pattern metrics to land-cover misclassification and differences in land-cover composition

Treesearch

James D. Wickham; Robert V. O' Neill; Kurt H. Riitters; Timothy G. Wade; K. Bruce Jones

1997-01-01

Calculation of landscape metrics from land-cover data is becoming increasingly common. Some studies have shown that these measurements are sensitive to differences in land-cover composition, but none are known to have tested also their a sensitivity to land-cover misclassification. An error simulation model was written to test the sensitivity of selected land-scape...

Research priorities in land use and land-cover change for the Earth system and integrated assessment modelling

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

Hibbard, Kathleen A.; Janetos, Anthony C.; Van Vuuren, Detlef

2010-11-15

This special issue has highlighted recent and innovative methods and results that integrate observations and AQ3 modelling analyses of regional to global aspect of biophysical and biogeochemical interactions of land-cover change with the climate system. Both the Earth System and the Integrated Assessment modeling communities recognize the importance of an accurate representation of land use and land-cover change to understand and quantify the interactions and feedbacks with the climate and socio-economic systems, respectively. To date, cooperation between these communities has been limited. Based on common interests, this work discusses research priorities in representing land use and land-cover change for improvedmore » collaboration across modelling, observing and measurement communities. Major research topics in land use and land-cover change are those that help us better understand (1) the interaction of land use and land cover with the climate system (e.g. carbon cycle feedbacks), (2) the provision of goods and ecosystem services by terrestrial (natural and anthropogenic) land-cover types (e.g. food production), (3) land use and management decisions and (4) opportunities and limitations for managing climate change (for both mitigation and adaptation strategies).« less

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...

A Simple Model to Describe the Relationship among Rainfall, Groundwater and Land Subsidence under a Heterogeneous Aquifer

NASA Astrophysics Data System (ADS)

Zheng, Y. Y.; Chen, Y. L.; Lin, H. R.; Huang, S. Y.; Yeh, T. C. J.; Wen, J. C.

2017-12-01

Land subsidence is a very serious problem of Zhuoshui River alluvial fan, Taiwan. The main reason of land subsidence is a compression of soil, but the compression measured in the wide area is very extensive (Maryam et al., 2013; Linlin et al., 2014). Chen et al. [2010] studied the linear relationship between groundwater level and subsurface altitude variations from Global Positioning System (GPS) station in Zhuoshui River alluvial fan. But the subsurface altitude data were only from two GPS stations. Their distributions are spared and small, not enough to express the altitude variations of Zhuoshui River alluvial fan. Hung et al. [2011] used Interferometry Synthetic Aperture Radar (InSAR) to measure the surface subsidence in Zhuoshui River alluvial fan, but haven't compared with groundwater level. The study compares the correlation between rainfall events and groundwater level and compares the correlation between groundwater level and subsurface altitude, these two correlation affected by heterogeneous soil. From these relationships, a numerical model is built to simulate the land subsidence variations and estimate the coefficient of aquifer soil compressibility. Finally, the model can estimate the long-term land subsidence. Keywords: Land Subsidence, InSAR, Groundwater Level, Numerical Model, Correlation Analyses

Aeroacoustic Evaluation of Flap and Landing Gear Noise Reduction Concepts

NASA Technical Reports Server (NTRS)

Khorrami, Mehdi R.; Humphreys, William M., Jr.; Lockard, David P.; Ravetta, Patricio A.

2014-01-01

Aeroacoustic measurements for a semi-span, 18% scale, high-fidelity Gulfstream aircraft model are presented. The model was used as a test bed to conduct detailed studies of flap and main landing gear noise sources and to determine the effectiveness of numerous noise mitigation concepts. Using a traversing microphone array in the flyover direction, an extensive set of acoustic data was obtained in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel with the facility in the acoustically treated open-wall (jet) mode. Most of the information was acquired with the model in a landing configuration with the flap deflected 39 deg and the main landing gear alternately installed and removed. Data were obtained at Mach numbers of 0.16, 0.20, and 0.24 over directivity angles between 56 deg and 116 deg, with 90 deg representing the overhead direction. Measured acoustic spectra showed that several of the tested flap noise reduction concepts decrease the sound pressure levels by 2 - 4 dB over the entire frequency range at all directivity angles. Slightly lower levels of noise reduction from the main landing gear were obtained through the simultaneous application of various gear devices. Measured aerodynamic forces indicated that the tested gear/flap noise abatement technologies have a negligible impact on the aerodynamic performance of the aircraft model.

Landing Gear Components Noise Study - PIV and Hot-Wire Measurements

NASA Technical Reports Server (NTRS)

Hutcheson, Florence V.; Burley, Casey L.; Stead, Daniel J.; Becker, Lawrence E.; Price, Jennifer L.

2010-01-01

PIV and hot-wire measurements of the wake flow from rods and bars are presented. The test models include rods of different diameters and cross sections and a rod juxtaposed to a plate. The latter is representative of the latch door that is attached to an aircraft landing gear when the gear is deployed, while the single and multiple rod configurations tested are representative of some of the various struts and cables configuration present on an aircraft landing gear. The test set up is described and the flow measurements are presented. The effect of model surface treatment and freestream turbulence on the spanwise coherence of the vortex shedding is studied for several rod and bar configurations.

Extending the Confrontation of Weather and Climate Models from Soil Moisture to Surface Flux Data

NASA Astrophysics Data System (ADS)

Dirmeyer, P.; Chen, L.; Wu, J.

2016-12-01

The atmosphere and land components of weather and climate models are typically developed separately and coupled as a last step before new model versions are released. Separate testing of land surface models (LSMs) and atmospheric models is often quite extensive in the development phase, but validation of coupled land-atmosphere behavior is often minimal if performed at all. This is partly because of this piecemeal model development approach and partly because the necessary in situ data to confront coupled land-atmosphere models (LAMs) has been meager until quite recently. Over the past 10-20 years there has been a growing number of networks of measurements of land surface states, surface fluxes, radiation and near-surface meteorology, although they have been largely uncoordinated and frequently incomplete across the range of variables necessary to validate LAMs. We extend recent work "confronting" a variety of LSMs and LAMs with in situ observations of soil moisture from cross-standardized networks to comparisons with measurements of surface latent and sensible heat fluxes at FLUXNET sites in a variety of climate regimes around the world. The motivation is to determine how well LSMs represent observed statistics of variability and co-variability, how much models differ from one another, and how those statistics change when the LSMs are coupled to atmospheric models. Furthermore, comparisons are made to several LAMs in both open-loop (free running) and reanalysis configurations. This shows to what extent data assimilation can constrain the processes involved in flux variability, and helps illuminate model development pathways to improve coupled land-atmosphere interactions in weather and climate models.

Use of coastal altimeter and tide gauge data for a seamless land-sea vertical datum in Taiwan

NASA Astrophysics Data System (ADS)

Yen-Ti, C.; Hwang, C.

2017-12-01

Conventional topographic and hydrographic mappings use two separate reference surfaces, called orthometric datum (TWVD2001 in Taiwan) and chart datum. In Taiwan, land elevations are heights tied to a leveling control network with its zero height at the mean sea surface of Keelung Harbor (realized by the height of Benchmark K999). Ocean depths are counted from the lowest tidal surface defined by tidal measurements near the sites of depth measurements. This paper usesa new method to construct a unified vertical datum for land elevations and ocean depths around Taiwan. First, we determine an optimal mean sea surface model (MSSHM) using refined offshore altimeter data. Then, the ellipsoidal heights of the mean sea levels at 36 tide gauges around Taiwan are determined using GPS measurements at their nearby benchmarks, and are then combined with the altimeter-derived MSSHM to generate a final MSSHM that has a smooth transition from land to sea. We also construct an improved ocean tide model to obtain various tidal surfaces. Using the latest land, shipborne, airborne and altimeter-derived gravity data, we construct a hybrid geoid model to define a vertical datum on land. The final MSSHM is the zero surface that defines ocean tidal heights and lowest tidal values in a ellipsoidal system that is fully consistent with the geodetic system of GNSS. The use of the MSSHM and the hybrid geoid model enables a seamless connection to combine or compare coastal land and sea elevations from a wide range of sources.

The international soil moisture network: A data hosting facility for global in situ soil moisture measurements

USDA-ARS?s Scientific Manuscript database

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land co...

An econometric analysis of changes in arable land utilization using multinomial logit model in Pinggu district, Beijing, China.

PubMed

Xu, Yueqing; McNamara, Paul; Wu, Yanfang; Dong, Yue

2013-10-15

Arable land in China has been decreasing as a result of rapid population growth and economic development as well as urban expansion, especially in developed regions around cities where quality farmland quickly disappears. This paper analyzed changes in arable land utilization during 1993-2008 in the Pinggu district, Beijing, China, developed a multinomial logit (MNL) model to determine spatial driving factors influencing arable land-use change, and simulated arable land transition probabilities. Land-use maps, as well as social-economic and geographical data were used in the study. The results indicated that arable land decreased significantly between 1993 and 2008. Lost arable land shifted into orchard, forestland, settlement, and transportation land. Significant differences existed for arable land transitions among different landform areas. Slope, elevation, population density, urbanization rate, distance to settlements, and distance to roadways were strong drivers influencing arable land transition to other uses. The MNL model was proved effective for predicting transition probabilities in land use from arable land to other land-use types, thus can be used for scenario analysis to develop land-use policies and land-management measures in this metropolitan area. Copyright © 2013 Elsevier Ltd. All rights reserved.

Airborne Two-Micron Double-Pulse IPDA Lidar Validation for Carbon Dioxide Measurements Over Land

NASA Astrophysics Data System (ADS)

Refaat, Tamer F.; Singh, Upendra N.; Yu, Jirong; Petros, Mulugeta; Remus, Ruben; Ismail, Syed

2018-04-01

An airborne double-pulse 2-μm Integrated Path Differential Absorption (IPDA) lidar has been developed at NASA LaRC for measuring atmospheric CO2. IPDA was validated using NASA B-200 aircraft over land and ocean under different conditions. IPDA evaluation for land vegetation returns, during full day background conditions, are presented. IPDA CO2 measurements compare well with model results driven from on-board insitu sensor data. These results also indicate that CO2 measurement bias is consistent with that from ocean surface returns.

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.

Evaluation of improved land use data and canopy representation in BEIS with biogenic VOC measurements in California

EPA Pesticide Factsheets

The link provided access to all the datasets and metadata used in this manuscript for the model development and evaluation per Geoscientific Model Development's publication guidelines with the exception of the model output due to its size. This dataset is associated with the following publication:Bash , J., K. Baker , and M. Beaver. Evaluation of improved land use and canopy representation in BEIS v3.61 with biogenic VOC measurements in California. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 9: 2191-2207, (2016).

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.

Artificial neural network modeling of the water quality index using land use areas as predictors.

PubMed

Gazzaz, Nabeel M; Yusoff, Mohd Kamil; Ramli, Mohammad Firuz; Juahir, Hafizan; Aris, Ahmad Zaharin

2015-02-01

This paper describes the design of an artificial neural network (ANN) model to predict the water quality index (WQI) using land use areas as predictors. Ten-year records of land use statistics and water quality data for Kinta River (Malaysia) were employed in the modeling process. The most accurate WQI predictions were obtained with the network architecture 7-23-1; the back propagation training algorithm; and a learning rate of 0.02. The WQI forecasts of this model had significant (p < 0.01), positive, very high correlation (ρs = 0.882) with the measured WQI values. Sensitivity analysis revealed that the relative importance of the land use classes to WQI predictions followed the order: mining > rubber > forest > logging > urban areas > agriculture > oil palm. These findings show that the ANNs are highly reliable means of relating water quality to land use, thus integrating land use development with river water quality management.

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.

Prediction of Landing Gear Noise Reduction and Comparison to Measurements

NASA Technical Reports Server (NTRS)

Lopes, Leonard V.

2010-01-01

Noise continues to be an ongoing problem for existing aircraft in flight and is projected to be a concern for next generation designs. During landing, when the engines are operating at reduced power, the noise from the airframe, of which landing gear noise is an important part, is equal to the engine noise. There are several methods of predicting landing gear noise, but none have been applied to predict the change in noise due to a change in landing gear design. The current effort uses the Landing Gear Model and Acoustic Prediction (LGMAP) code, developed at The Pennsylvania State University to predict the noise from landing gear. These predictions include the influence of noise reduction concepts on the landing gear noise. LGMAP is compared to wind tunnel experiments of a 6.3%-scale Boeing 777 main gear performed in the Quiet Flow Facility (QFF) at NASA Langley. The geometries tested in the QFF include the landing gear with and without a toboggan fairing and the door. It is shown that LGMAP is able to predict the noise directives and spectra from the model-scale test for the baseline configuration as accurately as current gear prediction methods. However, LGMAP is also able to predict the difference in noise caused by the toboggan fairing and by removing the landing gear door. LGMAP is also compared to far-field ground-based flush-mounted microphone measurements from the 2005 Quiet Technology Demonstrator 2 (QTD 2) flight test. These comparisons include a Boeing 777-300ER with and without a toboggan fairing that demonstrate that LGMAP can be applied to full-scale flyover measurements. LGMAP predictions of the noise generated by the nose gear on the main gear measurements are also shown.

International land Model Benchmarking (ILAMB) Package v002.00

DOE Data Explorer

Collier, Nathaniel [Oak Ridge National Laboratory; Hoffman, Forrest M. [Oak Ridge National Laboratory; Mu, Mingquan [University of California, Irvine; Randerson, James T. [University of California, Irvine; Riley, William J. [Lawrence Berkeley National Laboratory

2016-05-09

As a contribution to International Land Model Benchmarking (ILAMB) Project, we are providing new analysis approaches, benchmarking tools, and science leadership. The goal of ILAMB is to assess and improve the performance of land models through international cooperation and to inform the design of new measurement campaigns and field studies to reduce uncertainties associated with key biogeochemical processes and feedbacks. ILAMB is expected to be a primary analysis tool for CMIP6 and future model-data intercomparison experiments. This team has developed initial prototype benchmarking systems for ILAMB, which will be improved and extended to include ocean model metrics and diagnostics.

International land Model Benchmarking (ILAMB) Package v001.00

DOE Data Explorer

Mu, Mingquan [University of California, Irvine; Randerson, James T. [University of California, Irvine; Riley, William J. [Lawrence Berkeley National Laboratory; Hoffman, Forrest M. [Oak Ridge National Laboratory

2016-05-02

As a contribution to International Land Model Benchmarking (ILAMB) Project, we are providing new analysis approaches, benchmarking tools, and science leadership. The goal of ILAMB is to assess and improve the performance of land models through international cooperation and to inform the design of new measurement campaigns and field studies to reduce uncertainties associated with key biogeochemical processes and feedbacks. ILAMB is expected to be a primary analysis tool for CMIP6 and future model-data intercomparison experiments. This team has developed initial prototype benchmarking systems for ILAMB, which will be improved and extended to include ocean model metrics and diagnostics.

Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Zaitchik, Benjamin F.; Rodell, Matt

2008-01-01

The NASA Gravity Recovery and Climate Experiment (GRACE) system of satellites provides observations of large-scale, monthly terrestrial water storage (TWS) changes. In. this presentation we describe a land data assimilation system that ingests GRACE observations and show that the assimilation improves estimates of water storage and fluxes, as evaluated against independent measurements. The ensemble-based land data assimilation system uses a Kalman smoother approach along with the NASA Catchment Land Surface Model (CLSM). We assimilated GRACE-derived TWS anomalies for each of the four major sub-basins of the Mississippi into the Catchment Land Surface Model (CLSM). Compared with the open-loop (no assimilation) CLSM simulation, assimilation estimates of groundwater variability exhibited enhanced skill with respect to measured groundwater. Assimilation also significantly increased the correlation between simulated TWS and gauged river flow for all four sub-basins and for the Mississippi River basin itself. In addition, model performance was evaluated for watersheds smaller than the scale of GRACE observations, in the majority of cases, GRACE assimilation led to increased correlation between TWS estimates and gauged river flow, indicating that data assimilation has considerable potential to downscale GRACE data for hydrological applications. We will also describe how the output from the GRACE land data assimilation system is now being prepared for use in the North American Drought Monitor.

On the Land-Ocean Contrast of Tropical Convection and Microphysics Statistics Derived from TRMM Satellite Signals and Global Storm-Resolving Models

NASA Technical Reports Server (NTRS)

Matsui, Toshihisa; Chern, Jiun-Dar; Tao, Wei-Kuo; Lang, Stephen E.; Satoh, Masaki; Hashino, Tempei; Kubota, Takuji

2016-01-01

A 14-year climatology of Tropical Rainfall Measuring Mission (TRMM) collocated multi-sensor signal statistics reveal a distinct land-ocean contrast as well as geographical variability of precipitation type, intensity, and microphysics. Microphysics information inferred from the TRMM precipitation radar and Microwave Imager (TMI) show a large land-ocean contrast for the deep category, suggesting continental convective vigor. Over land, TRMM shows higher echo-top heights and larger maximum echoes, suggesting taller storms and more intense precipitation, as well as larger microwave scattering, suggesting the presence of morelarger frozen convective hydrometeors. This strong land-ocean contrast in deep convection is invariant over seasonal and multi-year time-scales. Consequently, relatively short-term simulations from two global storm-resolving models can be evaluated in terms of their land-ocean statistics using the TRMM Triple-sensor Three-step Evaluation via a satellite simulator. The models evaluated are the NASA Multi-scale Modeling Framework (MMF) and the Non-hydrostatic Icosahedral Cloud Atmospheric Model (NICAM). While both simulations can represent convective land-ocean contrasts in warm precipitation to some extent, near-surface conditions over land are relatively moisture in NICAM than MMF, which appears to be the key driver in the divergent warm precipitation results between the two models. Both the MMF and NICAM produced similar frequencies of large CAPE between land and ocean. The dry MMF boundary layer enhanced microwave scattering signals over land, but only NICAM had an enhanced deep convection frequency over land. Neither model could reproduce a realistic land-ocean contrast in in deep convective precipitation microphysics. A realistic contrast between land and ocean remains an issue in global storm-resolving modeling.

Global Modeling, Field Campaigns, Upscaling and Ray Desjardins

NASA Technical Reports Server (NTRS)

Sellers, P. J.; Hall, F. G.

2012-01-01

In the early 1980's, it became apparent that land surface radiation and energy budgets were unrealistically represented in Global Circulation models (GCM's), Shortly thereafter, it became clear that the land carbon budget was also poorly represented in Earth System Models (ESM's), A number of scientific communities, including GCM/ESM modelers, micrometeorologists, satellite data specialists and plant physiologists, came together to design field experiments that could be used to develop and validate the contemporary prototype land surface models. These experiments were designed to measure land surface fluxes of radiation, heat, water vapor and CO2 using a network of flux towers and other plot-scale techniques, coincident with satellite measurements of related state variables, The interdisciplinary teams involved in these experiments quickly became aware of the scale gap between plot-scale measurements (approx 10 - 100m), satellite measurements (100m - 10 km), and GCM grid areas (l0 - 200km). At the time, there was no established flux measurement capability to bridge these scale gaps. Then, a Canadian science learn led by Ray Desjardins started to actively participate in the design and execution of the experiments, with airborne eddy correlation providing the radically innovative bridge across the scale gaps, In a succession of brilliantly executed field campaigns followed up by convincing scientific analyses, they demonstrated that airborne eddy correlation allied with satellite data was the most powerful upscaling tool available to the community, The rest is history: the realism and credibility of weather and climate models has been enormously improved enormously over the last 25 years with immense benefits to the public and policymakers.

Linking land cover and water quality in New York City's water supply watersheds.

PubMed

Mehaffey, M H; Nash, M S; Wade, T G; Ebert, D W; Jones, K B; Rager, A

2005-08-01

The Catskill/Delaware reservoirs supply 90% of New York City's drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.

Flood risk in a changing world - a coupled transdisciplinary modelling framework for flood risk assessment in an Alpine study area

NASA Astrophysics Data System (ADS)

Huttenlau, Matthias; Schneeberger, Klaus; Winter, Benjamin; Pazur, Robert; Förster, Kristian; Achleitner, Stefan; Bolliger, Janine

2017-04-01

Devastating flood events have caused substantial economic damage across Europe during past decades. Flood risk management has therefore become a topic of crucial interest across state agencies, research communities and the public sector including insurances. There is consensus that mitigating flood risk relies on impact assessments which quantitatively account for a broad range of aspects in a (changing) environment. Flood risk assessments which take into account the interaction between the drivers climate change, land-use change and socio-economic change might bring new insights to the understanding of the magnitude and spatial characteristic of flood risks. Furthermore, the comparative assessment of different adaptation measures can give valuable information for decision-making. With this contribution we present an inter- and transdisciplinary research project aiming at developing and applying such an impact assessment relying on a coupled modelling framework for the Province of Vorarlberg in Austria. Stakeholder engagement ensures that the final outcomes of our study are accepted and successfully implemented in flood management practice. The study addresses three key questions: (i) What are scenarios of land- use and climate change for the study area? (ii) How will the magnitude and spatial characteristic of future flood risk change as a result of changes in climate and land use? (iii) Are there spatial planning and building-protection measures which effectively reduce future flood risk? The modelling framework has a modular structure comprising modules (i) climate change, (ii) land-use change, (iii) hydrologic modelling, (iv) flood risk analysis, and (v) adaptation measures. Meteorological time series are coupled with spatially explicit scenarios of land-use change to model runoff time series. The runoff time series are combined with impact indicators such as building damages and results are statistically assessed to analyse flood risk scenarios. Thus, the regional flood risk can be expressed in terms of expected annual damage and damages associated with a low probability of occurrence. We consider building protection measures explicitly as part of the consequence analysis of flood risk whereas spatial planning measures are already considered as explicit scenarios in the course of land-use change modelling.

AERO: A Decision Support Tool for Wind Erosion Assessment in Rangelands and Croplands

NASA Astrophysics Data System (ADS)

Galloza, M.; Webb, N.; Herrick, J.

2015-12-01

Wind erosion is a key driver of global land degradation, with on- and off-site impacts on agricultural production, air quality, ecosystem services and climate. Measuring rates of wind erosion and dust emission across land use and land cover types is important for quantifying the impacts and identifying and testing practical management options. This process can be assisted by the application of predictive models, which can be a powerful tool for land management agencies. The Aeolian EROsion (AERO) model, a wind erosion and dust emission model interface provides access by non-expert land managers to a sophisticated wind erosion decision-support tool. AERO incorporates land surface processes and sediment transport equations from existing wind erosion models and was designed for application with available national long-term monitoring datasets (e.g. USDI BLM Assessment, Inventory and Monitoring, USDA NRCS Natural Resources Inventory) and monitoring protocols. Ongoing AERO model calibration and validation are supported by geographically diverse data on wind erosion rates and land surface conditions collected by the new National Wind Erosion Research Network. Here we present the new AERO interface, describe parameterization of the underpinning wind erosion model, and provide a summary of the model applications across agricultural lands and rangelands in the United States.

Impact of water use efficiency on eddy covariance flux partitioning using correlation structure analysis

USDA-ARS?s Scientific Manuscript database

Partitioned land surfaces fluxes (e.g. evaporation, transpiration, photosynthesis, and ecosystem respiration) are needed as input, calibration, and validation data for numerous hydrological and land surface models. However, one of the most commonly used techniques for measuring land surface fluxes,...

Microwave Brightness Of Land Surfaces From Outer Space

NASA Technical Reports Server (NTRS)

Kerr, Yann H.; Njoku, Eni G.

1991-01-01

Mathematical model approximates microwave radiation emitted by land surfaces traveling to microwave radiometer in outer space. Applied to measurements made by Scanning Multichannel Microwave Radiometer (SMMR). Developed for interpretation of microwave imagery of Earth to obtain distributions of various chemical, physical, and biological characteristics across its surface. Intended primarily for use in mapping moisture content of soil and fraction of Earth covered by vegetation. Advanced Very-High-Resolution Radiometer (AVHRR), provides additional information on vegetative cover, thereby making possible retrieval of soil-moisture values from SMMR measurements. Possible to monitor changes of land surface during intervals of 5 to 10 years, providing significant data for mathematical models of evolution of climate.

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 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.

Characteristics and Impact of Imperviousness From a GIS-based Hydrological Perspective

NASA Astrophysics Data System (ADS)

Moglen, G. E.; Kim, S.

2005-12-01

With the concern that imperviousness can be differently quantified depending on data sources and methods, this study assessed imperviousness estimates using two different data sources: land use and land cover. Year 2000 land use developed by the Maryland Department of Planning was utilized to estimate imperviousness by assigning imperviousness coefficients to unique land use categories. These estimates were compared with imperviousness estimates based on satellite-derived land cover from the 2001 National Land Cover Dataset. Our study developed the relationships between these two estimates in the form of regression equations to convert imperviousness derived from one data source to the other. The regression equations are considered reliable, based on goodness-of-fit measures. Furthermore, this study examined how quantitatively different imperviousness estimates affect the prediction of hydrological response both in the flow regime and in the thermal regime. We assessed the relationships between indicators of hydrological response and imperviousness-descriptors. As indicators of flow variability, coefficient of variance, lag-one autocorrelation, and mean daily flow change were calculated based on measured mean daily stream flow from the water year 1997 to 2003. For thermal variability, indicators such as percent-days of surge, degree-day, and mean daily temperature difference were calculated base on measured stream temperature over several basins in Maryland. To describe imperviousness through the hydrological process, GIS-based spatially distributed hydrological models were developed based on a water-balance method and the SCS-CN method. Imperviousness estimates from land use and land cover were used as predictors in these models to examine the effect of imperviousness using different data sources on the prediction of hydrological response. Indicators of hydrological response were also regressed on aggregate imperviousness. This allowed for identifying if hydrological response is more sensitive to spatially distributed imperviousness or aggregate (lumped) imperviousness. The regressions between indicators of hydrological response and imperviousness-descriptors were evaluated by examining goodness-of-fit measures such as explained variance or relative standard error. The results show that imperviousness estimates using land use are better predictors of flow variability and thermal variability than imperviousness estimates using land cover. Also, this study reveals that flow variability is more sensitive to spatially distributed models than lumped models, while thermal variability is equally responsive to both models. The findings from this study can be further examined from a policy perspective with regard to policies that are based on a threshold concept for imperviousness impacts on the ecological and hydrological system.

Simulating soil organic carbon stock as affected by land cover change and climate change, Hyrcanian forests (northern Iran).

PubMed

Soleimani, Azam; Hosseini, Seyed Mohsen; Massah Bavani, Ali Reza; Jafari, Mostafa; Francaviglia, Rosa

2017-12-01

Soil organic carbon (SOC) contains a considerable portion of the world's terrestrial carbon stock, and is affected by changes in land cover and climate. SOC modeling is a useful approach to assess the impact of land use, land use change and climate change on carbon (C) sequestration. This study aimed to: (i) test the performance of RothC model using data measured from different land covers in Hyrcanian forests (northern Iran); and (ii) predict changes in SOC under different climate change scenarios that may occur in the future. The following land covers were considered: Quercus castaneifolia (QC), Acer velutinum (AV), Alnus subcordata (AS), Cupressus sempervirens (CS) plantations and a natural forest (NF). For assessment of future climate change projections the Fifth Assessment IPCC report was used. These projections were generated with nine Global Climate Models (GCMs), for two Representative Concentration Pathways (RCPs) leading to very low and high greenhouse gases concentration levels (RCP 2.6 and RCP 8.5 respectively), and for four 20year-periods up to 2099 (2030s, 2050s, 2070s and 2090s). Simulated values of SOC correlated well with measured data (R 2 =0.64 to 0.91) indicating a good efficiency of the RothC model. Our results showed an overall decrease in SOC stocks by 2099 under all land covers and climate change scenarios, but the extent of the decrease varied with the climate models, the emissions scenarios, time periods and land covers. Acer velutinum plantation was the most sensitive land cover to future climate change (range of decrease 8.34-21.83tCha -1 ). Results suggest that modeling techniques can be effectively applied for evaluating SOC stocks, allowing the identification of current patterns in the soil and the prediction of future conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Scenario-Led Habitat Modelling of Land Use Change Impacts on Key Species

PubMed Central

Geary, Matthew; Fielding, Alan H.; McGowan, Philip J. K.; Marsden, Stuart J.

2015-01-01

Accurate predictions of the impacts of future land use change on species of conservation concern can help to inform policy-makers and improve conservation measures. If predictions are spatially explicit, predicted consequences of likely land use changes could be accessible to land managers at a scale relevant to their working landscape. We introduce a method, based on open source software, which integrates habitat suitability modelling with scenario-building, and illustrate its use by investigating the effects of alternative land use change scenarios on landscape suitability for black grouse Tetrao tetrix. Expert opinion was used to construct five near-future (twenty years) scenarios for the 800 km2 study site in upland Scotland. For each scenario, the cover of different land use types was altered by 5–30% from 20 random starting locations and changes in habitat suitability assessed by projecting a MaxEnt suitability model onto each simulated landscape. A scenario converting grazed land to moorland and open forestry was the most beneficial for black grouse, and ‘increased grazing’ (the opposite conversion) the most detrimental. Positioning of new landscape blocks was shown to be important in some situations. Increasing the area of open-canopy forestry caused a proportional decrease in suitability, but suitability gains for the ‘reduced grazing’ scenario were nonlinear. ‘Scenario-led’ landscape simulation models can be applied in assessments of the impacts of land use change both on individual species and also on diversity and community measures, or ecosystem services. A next step would be to include landscape configuration more explicitly in the simulation models, both to make them more realistic, and to examine the effects of habitat placement more thoroughly. In this example, the recommended policy would be incentives on grazing reduction to benefit black grouse. PMID:26569604

Improving the Representation of Land in Climate Models by Application of EOS Observations

NASA Technical Reports Server (NTRS)

2004-01-01

The PI's IDS current and previous investigation has focused on the applications of the land data toward the improvement of climate models. The previous IDS research identified the key factors limiting the accuracy of climate models to be the representation of albedos, land cover, fraction of landscape covered by vegetation, roughness lengths, surface skin temperature and canopy properties such as leaf area index (LAI) and average stomatal conductance. Therefore, we assembled a team uniquely situated to focus on these key variables and incorporate the remotely sensed measures of these variables into the next generation of climate models.

The Carbon-Land Model Intercomparison Project (C-LAMP): A Model-Data Comparison System for Evaluation of Coupled Biosphere-Atmosphere Models

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

Hoffman, Forrest M; Randerson, Jim; Thornton, Peter E

2009-01-01

The need to capture important climate feebacks in general circulation models (GCMs) has resulted in new efforts to include atmospheric chemistry and land and ocean biogeochemistry into the next generation of production climate models, now often referred to as Earth System Models (ESMs). While many terrestrial and ocean carbon models have been coupled to GCMs, recent work has shown that such models can yield a wide range of results, suggesting that a more rigorous set of offline and partially coupled experiments, along with detailed analyses of processes and comparisons with measurements, are warranted. The Carbon-Land Model Intercomparison Project (C-LAMP) providesmore » a simulation protocol and model performance metrics based upon comparisons against best-available satellite- and ground-based measurements (Hoffman et al., 2007). C-LAMP provides feedback to the modeling community regarding model improvements and to the measurement community by suggesting new observational campaigns. C-LAMP Experiment 1 consists of a set of uncoupled simulations of terrestrial carbon models specifically designed to examine the ability of the models to reproduce surface carbon and energy fluxes at multiple sites and to exhibit the influence of climate variability, prescribed atmospheric carbon dioxide (CO{sub 2}), nitrogen (N) deposition, and land cover change on projections of terrestrial carbon fluxes during the 20th century. Experiment 2 consists of partially coupled simulations of the terrestrial carbon model with an active atmosphere model exchanging energy and moisture fluxes. In all experiments, atmospheric CO{sub 2} follows the prescribed historical trajectory from C{sup 4}MIP. In Experiment 2, the atmosphere model is forced with prescribed sea surface temperatures (SSTs) and corresponding sea ice concentrations from the Hadley Centre; prescribed CO{sub 2} is radiatively active; and land, fossil fuel, and ocean CO{sub 2} fluxes are advected by the model. Both sets of experiments have been performed using two different terrestrial biogeochemistry modules coupled to the Community Land Model version 3 (CLM3) in the Community Climate System Model version 3 (CCSM3): The CASA model of Fung, et al., and the carbon-nitrogen (CN) model of Thornton. Comparisons against Ameriflus site measurements, MODIS satellite observations, NOAA flask records, TRANSCOM inversions, and Free Air CO{sub 2} Enrichment (FACE) site measurements, and other datasets have been performed and are described in Randerson et al. (2009). The C-LAMP diagnostics package was used to validate improvements to CASA and CN for use in the next generation model, CLM4. It is hoped that this effort will serve as a prototype for an international carbon-cycle model benchmarking activity for models being used for the Inter-governmental Panel on Climate Change (IPCC) Fifth Assessment Report. More information about C-LAMP, the experimental protocol, performance metrics, output standards, and model-data comparisons from the CLM3-CASA and CLM3-CN models are available at http://www.climatemodeling.org/c-lamp.« less

Impact of Land Model Calibration on Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry and wet land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through calibration of the Noah land surface model using the new optimization and uncertainty estimation subsystem in NASA's Land Information System (LIS-OPT/UE). The impact of the calibration on the a) spinup of the land surface used as initial conditions, and b) the simulated heat and moisture states and fluxes of the coupled WRF simulations is then assessed. Changes in ambient weather and land-atmosphere coupling are evaluated along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Results indicate that the offline calibration leads to systematic improvements in land-PBL fluxes and near-surface temperature and humidity, and in the process provide guidance on the questions of what, how, and when to calibrate land surface models for coupled model prediction.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Estimating Demand for Industrial and Commercial Land Use Given Economic Forecasts

PubMed Central

Batista e Silva, Filipe; Koomen, Eric; Diogo, Vasco; Lavalle, Carlo

2014-01-01

Current developments in the field of land use modelling point towards greater level of spatial and thematic resolution and the possibility to model large geographical extents. Improvements are taking place as computational capabilities increase and socioeconomic and environmental data are produced with sufficient detail. Integrated approaches to land use modelling rely on the development of interfaces with specialized models from fields like economy, hydrology, and agriculture. Impact assessment of scenarios/policies at various geographical scales can particularly benefit from these advances. A comprehensive land use modelling framework includes necessarily both the estimation of the quantity and the spatial allocation of land uses within a given timeframe. In this paper, we seek to establish straightforward methods to estimate demand for industrial and commercial land uses that can be used in the context of land use modelling, in particular for applications at continental scale, where the unavailability of data is often a major constraint. We propose a set of approaches based on ‘land use intensity’ measures indicating the amount of economic output per existing areal unit of land use. A base model was designed to estimate land demand based on regional-specific land use intensities; in addition, variants accounting for sectoral differences in land use intensity were introduced. A validation was carried out for a set of European countries by estimating land use for 2006 and comparing it to observations. The models’ results were compared with estimations generated using the ‘null model’ (no land use change) and simple trend extrapolations. Results indicate that the proposed approaches clearly outperformed the ‘null model’, but did not consistently outperform the linear extrapolation. An uncertainty analysis further revealed that the models’ performances are particularly sensitive to the quality of the input land use data. In addition, unknown future trends of regional land use intensity widen considerably the uncertainty bands of the predictions. PMID:24647587

Aquarius Whole Range Calibration: Celestial Sky, Ocean, and Land Targets

NASA Technical Reports Server (NTRS)

Dinnat, Emmanuel P.; Le Vine, David M.; Bindlish, Rajat; Piepmeier, Jeffrey R.; Brown, Shannon T.

2014-01-01

Aquarius is a spaceborne instrument that uses L-band radiometers to monitor sea surface salinity globally. Other applications of its data over land and the cryosphere are being developed. Combining its measurements with existing and upcoming L-band sensors will allow for long term studies. For that purpose, the radiometers calibration is critical. Aquarius measurements are currently calibrated over the oceans. They have been found too cold at the low end (celestial sky) of the brightness temperature scale, and too warm at the warm end (land and ice). We assess the impact of the antenna pattern model on the biases and propose a correction. We re-calibrate Aquarius measurements using the corrected antenna pattern and measurements over the Sky and oceans. The performances of the new calibration are evaluated using measurements over well instrument land sites.

Estimates of Soil Moisture Using the Land Information System for Land Surface Water Storage: Case Study for the Western States Water Mission

NASA Astrophysics Data System (ADS)

Liu, P. W.; Famiglietti, J. S.; Levoe, S.; Reager, J. T., II; David, C. H.; Kumar, S.; Li, B.; Peters-Lidard, C. D.

2017-12-01

Soil moisture is one of the critical factors in terrestrial hydrology. Accurate soil moisture information improves estimation of terrestrial water storage and fluxes, that is essential for water resource management including sustainable groundwater pumping and agricultural irrigation practices. It is particularly important during dry periods when water stress is high. The Western States Water Mission (WSWM), a multiyear mission project of NASA's Jet Propulsion Laboratory, is operated to understand and estimate quantities of the water availability in the western United States by integrating observations and measurements from in-situ and remote sensing sensors, and hydrological models. WSWM data products have been used to assess and explore the adverse impacts of the California drought (2011-2016) and provide decision-makers information for water use planning. Although the observations are often more accurate, simulations using land surface models can provide water availability estimates at desired spatio-temporal scales. The Land Information System (LIS), developed by NASA's Goddard Space Flight Center, integrates developed land surface models and data processing and management tools, that enables to utilize the measurements and observations from various platforms as forcings in the high performance computing environment to forecast the hydrologic conditions. The goal of this study is to implement the LIS in the western United States for estimates of soil moisture. We will implement the NOAH-MP model at the 12km North America Land Data Assimilation System grid and compare to other land surface models included in the LIS. Findings will provide insight into the differences between model estimates and model physics. Outputs from a multi-model ensemble from LIS can also be used to enhance estimated reliability and provide quantification of uncertainty. We will compare the LIS-based soil moisture estimates to the SMAP enhanced 9 km soil moisture product to understand the mechanistic differences between the model and observation. These outcomes will contribute to the WSWM for providing robust products.

Evaluation of Land Suitability and Potential Production of Gambir Uncaria gambir Roxb. L) at Salido Saribulan, Pesisir Selatan Regency

NASA Astrophysics Data System (ADS)

Yuni, Juniarti

2017-04-01

Gambir (Uncaria gambir Roxb. L) is a specific commodity of export in West Sumatra. Area of Gambir tree increases about 8 % per year in West Sumatera and until 1998 its production increased about 17% per year. However, in 1999 its area does not parallel with its production. In the last five years, the volume of export increases about 82.81%, while its value of export reaches US 2.5/kg. Therefore, this commodity has a strategic value for city's earnings. One of predicted causes is the use of unappropriated land. The aim of this research is to measure levels of land suitability in the buffer zone. TNKS (The National Park Kerinci-Seblat) in order to get the area, which is suitable for growing commodity of Gambir tree. To evaluate land suitability, quantitative model from FAO is used by combining environmental data, climate and condition of land (physical and chemical characteristic of the land). Estimation of Radiation Thermal Production Potential (RPP). Every data is measured (rating) individually and included in several mathematical formulas. After that, potential production of a land based on climate (Climate Production Potential) = CPP) is obtained quantitatively. By changing certain variant of this model program, it can predict the result of the plant in another area. By entering the real data of a land plant production, this model can predict the real plant production of land (Land Production Potential= LPP). Salido Saribulan area is included in class of land suitability S3f which is suitable for growing Gambir tree with a limitation factor of nutrient retention. Potential of actual gambir production at Salido Saribulan is 5 ton/ha, which is higher than actual gambir production.

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.

Carbon Cycle Model Linkage Project (CCMLP): Evaluating Biogeochemical Process Models with Atmospheric Measurements and Field Experiments

NASA Astrophysics Data System (ADS)

Heimann, M.; Prentice, I. C.; Foley, J.; Hickler, T.; Kicklighter, D. W.; McGuire, A. D.; Melillo, J. M.; Ramankutty, N.; Sitch, S.

2001-12-01

Models of biophysical and biogeochemical proceses are being used -either offline or in coupled climate-carbon cycle (C4) models-to assess climate- and CO2-induced feedbacks on atmospheric CO2. Observations of atmospheric CO2 concentration, and supplementary tracers including O2 concentrations and isotopes, offer unique opportunities to evaluate the large-scale behaviour of models. Global patterns, temporal trends, and interannual variability of the atmospheric CO2 concentration and its seasonal cycle provide crucial benchmarks for simulations of regionally-integrated net ecosystem exchange; flux measurements by eddy correlation allow a far more demanding model test at the ecosystem scale than conventional indicators, such as measurements of annual net primary production; and large-scale manipulations, such as the Duke Forest Free Air Carbon Enrichment (FACE) experiment, give a standard to evaluate modelled phenomena such as ecosystem-level CO2 fertilization. Model runs including historical changes of CO2, climate and land use allow comparison with regional-scale monthly CO2 balances as inferred from atmospheric measurements. Such comparisons are providing grounds for some confidence in current models, while pointing to processes that may still be inadequately treated. Current plans focus on (1) continued benchmarking of land process models against flux measurements across ecosystems and experimental findings on the ecosystem-level effects of enhanced CO2, reactive N inputs and temperature; (2) improved representation of land use, forest management and crop metabolism in models; and (3) a strategy for the evaluation of C4 models in a historical observational context.

Wireless Channel Characterization: Modeling the 5 GHz Microwave Landing System Extension Band for Future Airport Surface Communications

NASA Technical Reports Server (NTRS)

Matolak, D. W.; Apaza, Rafael; Foore, Lawrence R.

2006-01-01

We describe a recently completed wideband wireless channel characterization project for the 5 GHz Microwave Landing System (MLS) extension band, for airport surface areas. This work included mobile measurements at large and small airports, and fixed point-to-point measurements. Mobile measurements were made via transmission from the air traffic control tower (ATCT), or from an airport field site (AFS), to a receiving ground vehicle on the airport surface. The point-to-point measurements were between ATCT and AFSs. Detailed statistical channel models were developed from all these measurements. Measured quantities include propagation path loss and power delay profiles, from which we obtain delay spreads, frequency domain correlation (coherence bandwidths), fading amplitude statistics, and channel parameter correlations. In this paper we review the project motivation, measurement coordination, and illustrate measurement results. Example channel modeling results for several propagation conditions are also provided, highlighting new findings.

The Parana paradox: can a model explain the decadal impacts of climate variability and land-cover change?

NASA Astrophysics Data System (ADS)

Lee, E.; Moorcroft, P. R.; Livino, A.; Briscoe, J.

2013-12-01

Since the 1970s, despite a decrease in rainfall, flow in the Parana river has increased. This paradox is explored using the Ecosystem Demography (ED) model. If there were no change in land cover, the modeled runoff decreased from the 1970s to the 2000s by 11.8% (with 1970 land cover) or 18.8% (with 2008 land cover). When the model is run holding climate constant, the decadal average of the modeled runoff increased by 24.4% (with the 1970s climate) or by 33.6% (with 2000s climate). When the model is run allowing both the actual climate and land-cover changes, the model gives an increase in the decadal average of runoff by 8.5%. This agrees well with 10.5% increase in the actual stream flow as measured at Itaipu. There are three main conclusions from this work. First, the ED model is able to explain a major, paradoxical, reality in the Parana basin. Second, it is necessary to take into account both climate and land use changes when exploring past or future changes in river flows. Third, the ED model, now coupled with a regional climate model (i.e., EDBRAMS), is a sound basis for exploring likely changes in river flows in major South American rivers.

Land Surface Precipitation and Hydrology in MERRA-2

NASA Technical Reports Server (NTRS)

Reichle, R.; Koster, R.; Draper, C.; Liu, Q.; Girotto, M.; Mahanama, S.; De Lannoy, G.; Partyka, G.

2017-01-01

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), provides global, 1-hourly estimates of land surface conditions for 1980-present at 50-km resolution. Outside of the high latitudes, MERRA-2 uses observations-based precipitation data products to correct the precipitation falling on the land surface. This paper describes the precipitation correction method and evaluates the MERRA-2 land surface precipitation and hydrology. Compared to monthly GPCPv2.2 observations, the corrected MERRA-2 precipitation (M2CORR) is better than the precipitation generated by the atmospheric models within the cyclingMERRA-2 system and the earlier MERRA reanalysis. Compared to 3-hourlyTRMM observations, the M2CORR diurnal cycle has better amplitude but less realistic phasing than MERRA-2 model-generated precipitation. Because correcting the precipitation within the coupled atmosphere-land modeling system allows the MERRA-2 near-surface air temperature and humidity to respond to the improved precipitation forcing, MERRA-2 provides more self-consistent surface meteorological data than were available from the earlier, offline MERRA-Land reanalysis. Overall, MERRA-2 land hydrology estimates are better than those of MERRA-Land and MERRA. A comparison against GRACE satellite observations of terrestrial water storage demonstrates clear improvements in MERRA-2 over MERRA in South America and Africa but also reflects known errors in the observations used to correct the MERRA-2 precipitation. The MERRA-2 and MERRA-Land surface and root zone soil moisture skill vs. in situ measurements is slightly higher than that of ERA-Interim Land and higher than that of MERRA (significantly for surface soil moisture). Snow amounts from MERRA-2 have lower bias and correlate better against reference data than do those of MERRA-Land and MERRA, with MERRA-2 skill roughly matching that of ERA-Interim Land. Seasonal anomaly R values against naturalized stream flow measurements in the United States are, on balance, highest for MERRA-2 and ERA-Interim Land, somewhat lower for MERRA-Land, and lower still for MERRA.

Global Precipitation Measurement (GPM) Ground Validation (GV) Science Implementation Plan

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Hou, Arthur Y.

2008-01-01

For pre-launch algorithm development and post-launch product evaluation Global Precipitation Measurement (GPM) Ground Validation (GV) goes beyond direct comparisons of surface rain rates between ground and satellite measurements to provide the means for improving retrieval algorithms and model applications.Three approaches to GPM GV include direct statistical validation (at the surface), precipitation physics validation (in a vertical columns), and integrated science validation (4-dimensional). These three approaches support five themes: core satellite error characterization; constellation satellites validation; development of physical models of snow, cloud water, and mixed phase; development of cloud-resolving model (CRM) and land-surface models to bridge observations and algorithms; and, development of coupled CRM-land surface modeling for basin-scale water budget studies and natural hazard prediction. This presentation describes the implementation of these approaches.

Using ARM Observations to Evaluate Climate Model Simulations of Land-Atmosphere Coupling on the U.S. Southern Great Plains

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

Phillips, Thomas J.; Klein, Stephen A.; Ma, Hsi -Yen

Several independent measurements of warm-season soil moisture and surface atmospheric variables recorded at the ARM Southern Great Plains (SGP) research facility are used to estimate the terrestrial component of land-atmosphere coupling (LAC) strength and its regional uncertainty. The observations reveal substantial variation in coupling strength, as estimated from three soil moisture measurements at a single site, as well as across six other sites having varied soil and land cover types. The observational estimates then serve as references for evaluating SGP terrestrial coupling strength in the Community Atmospheric Model coupled to the Community Land Model. These coupled model components are operatedmore » in both a free-running mode and in a controlled configuration, where the atmospheric and land states are reinitialized daily, so that they do not drift very far from observations. Although the controlled simulation deviates less from the observed surface climate than its free-running counterpart, the terrestrial LAC in both configurations is much stronger and displays less spatial variability than the SGP observational estimates. Preliminary investigation of vegetation leaf area index (LAI) substituted for soil moisture suggests that the overly strong coupling between model soil moisture and surface atmospheric variables is associated with too much evaporation from bare ground and too little from the vegetation cover. Lastly, these results imply that model surface characteristics such as LAI, as well as the physical parameterizations involved in the coupling of the land and atmospheric components, are likely to be important sources of the problematical LAC behaviors.« less

Using ARM Observations to Evaluate Climate Model Simulations of Land-Atmosphere Coupling on the U.S. Southern Great Plains

DOE PAGES

Phillips, Thomas J.; Klein, Stephen A.; Ma, Hsi -Yen; ...

2017-10-13

Several independent measurements of warm-season soil moisture and surface atmospheric variables recorded at the ARM Southern Great Plains (SGP) research facility are used to estimate the terrestrial component of land-atmosphere coupling (LAC) strength and its regional uncertainty. The observations reveal substantial variation in coupling strength, as estimated from three soil moisture measurements at a single site, as well as across six other sites having varied soil and land cover types. The observational estimates then serve as references for evaluating SGP terrestrial coupling strength in the Community Atmospheric Model coupled to the Community Land Model. These coupled model components are operatedmore » in both a free-running mode and in a controlled configuration, where the atmospheric and land states are reinitialized daily, so that they do not drift very far from observations. Although the controlled simulation deviates less from the observed surface climate than its free-running counterpart, the terrestrial LAC in both configurations is much stronger and displays less spatial variability than the SGP observational estimates. Preliminary investigation of vegetation leaf area index (LAI) substituted for soil moisture suggests that the overly strong coupling between model soil moisture and surface atmospheric variables is associated with too much evaporation from bare ground and too little from the vegetation cover. Lastly, these results imply that model surface characteristics such as LAI, as well as the physical parameterizations involved in the coupling of the land and atmospheric components, are likely to be important sources of the problematical LAC behaviors.« less

Comparing measured and modelled soil carbon: which site-specific variables are linked to high stability?

NASA Astrophysics Data System (ADS)

Robertson, Andy; Schipanski, Meagan; Ma, Liwang; Ahuja, Lajpat; McNamara, Niall; Smith, Pete; Davies, Christian

2016-04-01

Changes in soil carbon (C) stocks have been studied in depth over the last two decades, as net greenhouse gas (GHG) sinks are highlighted to be a partial solution to the causes of climate change. However, the stability of this soil C is often overlooked when measuring these changes. Ultimately a net sequestration in soils is far less beneficial if labile C is replacing more stable forms. To date there is no accepted framework for measuring soil C stability, and as a result there is considerable uncertainty associated with the simulated impacts of land management and land use change when using process-based systems models. However, a recent effort to equate measurable soil C fractions to model pools has generated data that help to assess the impacts of land management, and can ultimately help to reduce the uncertainty of model predictions. Our research compiles this existing fractionation data along with site metadata to create a simplistic statistical model able to quantify the relative importance of different site-specific conditions. Data was mined from 23 published studies and combined with original data to generate a dataset of 100+ land use change sites across Europe. For sites to be included they required soil C fractions isolated using the Zimmermann et al. (2007) method and specific site metadata (mean annual precipitation, MAP; mean annual temperature, MAT; soil pH; land use; altitude). Of the sites, 75% were used to develop a generalized linear mixed model (GLMM) to create coefficients where site parameters can be used to predict influence on the measured soil fraction C stocks. The remaining 25% of sites were used to evaluate uncertainty and validate this empirical model. Further, four of the aforementioned sites were used to simulate soil C dynamics using the RothC, DayCent and RZWQM2 models. A sensitivity analysis (4096 model runs for each variable applying Latin hypercube random sampling techniques) was then used to observe whether these models place as much weight on the same site parameters as the GLMM. Sites were spread across an extensive geographic area and encompassed a wide range of conditions (2% to 44% clay content; 0.9° C to 18° C MAT; 300mm to 1400mm MAP). Topsoil (30 cm) C stocks also varied considerably (29.0 to 115.9 t/ha) but the proportion deemed stable (mean residence time >10 years) was relatively consistent (72 ± 2 %). The GLMM approach suggested that an interaction of soil pH and historic land use explained the largest amount of variation seen in stable fraction C stocks, closely followed by MAT and MAP interactions. For all three systems models, the stable soil C pools were most sensitive to climatic variables and land use. However, RZWQM2 did indicate that soil characteristics (texture, pH) also had an influence on stable C pool dynamics. References 1 - Zimmermann et al., 2007. Measured soil organic matter fractions can be related to pools in the RothC model. European Journal of Soil Science, 58:658-667.

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

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Mocko, David M.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Xia, Youlong

2016-01-01

Model benchmarking allows us to separate uncertainty in model predictions caused 1 by model inputs from uncertainty due to model structural error. We extend this method with a large-sample approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances.

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions

PubMed Central

Nearing, Grey S.; Mocko, David M.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Xia, Youlong

2018-01-01

Model benchmarking allows us to separate uncertainty in model predictions caused by model inputs from uncertainty due to model structural error. We extend this method with a “large-sample” approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances. PMID:29697706

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions.

PubMed

Nearing, Grey S; Mocko, David M; Peters-Lidard, Christa D; Kumar, Sujay V; Xia, Youlong

2016-03-01

Model benchmarking allows us to separate uncertainty in model predictions caused by model inputs from uncertainty due to model structural error. We extend this method with a "large-sample" approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances.

Constraining a complex biogeochemical model for CO2 and N2O emission simulations from various land uses by model-data fusion

NASA Astrophysics Data System (ADS)

Houska, Tobias; Kraus, David; Kiese, Ralf; Breuer, Lutz

2017-07-01

This study presents the results of a combined measurement and modelling strategy to analyse N2O and CO2 emissions from adjacent arable land, forest and grassland sites in Hesse, Germany. The measured emissions reveal seasonal patterns and management effects, including fertilizer application, tillage, harvest and grazing. The measured annual N2O fluxes are 4.5, 0.4 and 0.1 kg N ha-1 a-1, and the CO2 fluxes are 20.0, 12.2 and 3.0 t C ha-1 a-1 for the arable land, grassland and forest sites, respectively. An innovative model-data fusion concept based on a multicriteria evaluation (soil moisture at different depths, yield, CO2 and N2O emissions) is used to rigorously test the LandscapeDNDC biogeochemical model. The model is run in a Latin-hypercube-based uncertainty analysis framework to constrain model parameter uncertainty and derive behavioural model runs. The results indicate that the model is generally capable of predicting trace gas emissions, as evaluated with RMSE as the objective function. The model shows a reasonable performance in simulating the ecosystem C and N balances. The model-data fusion concept helps to detect remaining model errors, such as missing (e.g. freeze-thaw cycling) or incomplete model processes (e.g. respiration rates after harvest). This concept further elucidates the identification of missing model input sources (e.g. the uptake of N through shallow groundwater on grassland during the vegetation period) and uncertainty in the measured validation data (e.g. forest N2O emissions in winter months). Guidance is provided to improve the model structure and field measurements to further advance landscape-scale model predictions.

Pairing FLUXNET sites to validate model representations of land-use/land-cover change

NASA Astrophysics Data System (ADS)

Chen, Liang; Dirmeyer, Paul A.; Guo, Zhichang; Schultz, Natalie M.

2018-01-01

Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.

Correspondence of biological condition models of California streams at statewide and regional scales.

PubMed

May, Jason T; Brown, Larry R; Rehn, Andrew C; Waite, Ian R; Ode, Peter R; Mazor, Raphael D; Schiff, Kenneth C

2015-01-01

We used boosted regression trees (BRT) to model stream biological condition as measured by benthic macroinvertebrate taxonomic completeness, the ratio of observed to expected (O/E) taxa. Models were developed with and without exclusion of rare taxa at a site. BRT models are robust, requiring few assumptions compared with traditional modeling techniques such as multiple linear regression. The BRT models were constructed to provide baseline support to stressor delineation by identifying natural physiographic and human land use gradients affecting stream biological condition statewide and for eight ecological regions within the state, as part of the development of numerical biological objectives for California's wadeable streams. Regions were defined on the basis of ecological, hydrologic, and jurisdictional factors and roughly corresponded with ecoregions. Physiographic and land use variables were derived from geographic information system coverages. The model for the entire state (n = 1,386) identified a composite measure of anthropogenic disturbance (the sum of urban, agricultural, and unmanaged roadside vegetation land cover) within the local watershed as the most important variable, explaining 56% of the variance in O/E values. Models for individual regions explained between 51 and 84% of the variance in O/E values. Measures of human disturbance were important in the three coastal regions. In the South Coast and Coastal Chaparral, local watershed measures of urbanization were the most important variables related to biological condition, while in the North Coast the composite measure of human disturbance at the watershed scale was most important. In the two mountain regions, natural gradients were most important, including slope, precipitation, and temperature. The remaining three regions had relatively small sample sizes (n ≤ 75 sites) and had models that gave mixed results. Understanding the spatial scale at which land use and land cover affect taxonomic completeness is imperative for sound management. Our results suggest that invertebrate taxonomic completeness is affected by human disturbance at the statewide and regional levels, with some differences among regions in the importance of natural gradients and types of human disturbance. The construction and application of models similar to the ones presented here could be useful in the planning and prioritization of actions for protection and conservation of biodiversity in California streams.

Correspondence of biological condition models of California streams at statewide and regional scales

USGS Publications Warehouse

May, Jason T.; Brown, Larry R.; Rehn, Andrew C.; Waite, Ian R.; Ode, Peter R; Mazor, Raphael D; Schiff, Kenneth C

2015-01-01

We used boosted regression trees (BRT) to model stream biological condition as measured by benthic macroinvertebrate taxonomic completeness, the ratio of observed to expected (O/E) taxa. Models were developed with and without exclusion of rare taxa at a site. BRT models are robust, requiring few assumptions compared with traditional modeling techniques such as multiple linear regression. The BRT models were constructed to provide baseline support to stressor delineation by identifying natural physiographic and human land use gradients affecting stream biological condition statewide and for eight ecological regions within the state, as part of the development of numerical biological objectives for California’s wadeable streams. Regions were defined on the basis of ecological, hydrologic, and jurisdictional factors and roughly corresponded with ecoregions. Physiographic and land use variables were derived from geographic information system coverages. The model for the entire state (n = 1,386) identified a composite measure of anthropogenic disturbance (the sum of urban, agricultural, and unmanaged roadside vegetation land cover) within the local watershed as the most important variable, explaining 56 % of the variance in O/E values. Models for individual regions explained between 51 and 84 % of the variance in O/E values. Measures of human disturbance were important in the three coastal regions. In the South Coast and Coastal Chaparral, local watershed measures of urbanization were the most important variables related to biological condition, while in the North Coast the composite measure of human disturbance at the watershed scale was most important. In the two mountain regions, natural gradients were most important, including slope, precipitation, and temperature. The remaining three regions had relatively small sample sizes (n ≤ 75 sites) and had models that gave mixed results. Understanding the spatial scale at which land use and land cover affect taxonomic completeness is imperative for sound management. Our results suggest that invertebrate taxonomic completeness is affected by human disturbance at the statewide and regional levels, with some differences among regions in the importance of natural gradients and types of human disturbance. The construction and application of models similar to the ones presented here could be useful in the planning and prioritization of actions for protection and conservation of biodiversity in California streams.

Socially optimal drainage system and agricultural biodiversity: a case study for Finnish landscape.

PubMed

Saikkonen, Liisa; Herzon, Irina; Ollikainen, Markku; Lankoski, Jussi

2014-12-15

This paper examines the socially optimal drainage choice (surface/subsurface) for agricultural crop cultivation in a landscape with different land qualities (fertilities) when private profits and nutrient runoff damages are taken into account. We also study the measurable social costs to increase biodiversity by surface drainage when the locations of the surface-drained areas in a landscape affect the provided biodiversity. We develop a general theoretical model and apply it to empirical data from Finnish agriculture. We find that for low land qualities the measurable social returns are higher to surface drainage than to subsurface drainage, and that the profitability of subsurface drainage increases along with land quality. The measurable social costs to increase biodiversity by surface drainage under low land qualities are negative. For higher land qualities, these costs depend on the land quality and on the biodiversity impacts. Biodiversity conservation plans for agricultural landscapes should focus on supporting surface drainage systems in areas where the measurable social costs to increase biodiversity are negative or lowest. Copyright © 2014 Elsevier Ltd. All rights reserved.

Parameterizing atmosphere-land surface exchange for climate models with satellite data: A case study for the Southern Great Plains CART site

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

Gao, W.

High-resolution satellite data provide detailed, quantitative descriptions of land surface characteristics over large areas so that objective scale linkage becomes feasible. With the aid of satellite data, Sellers et al. and Wood and Lakshmi examined the linearity of processes scaled up from 30 m to 15 km. If the phenomenon is scale invariant, then the aggregated value of a function or flux is equivalent to the function computed from aggregated values of controlling variables. The linear relation may be realistic for limited land areas having no large surface contrasts to cause significant horizontal exchange. However, for areas with sharp surfacemore » contrasts, horizontal exchange and different dynamics in the atmospheric boundary may induce nonlinear interactions, such as at interfaces of land-water, forest-farm land, and irrigated crops-desert steppe. The linear approach, however, represents the simplest scenario, and is useful for developing an effective scheme for incorporating subgrid land surface processes into large-scale models. Our studies focus on coupling satellite data and ground measurements with a satellite-data-driven land surface model to parameterize surface fluxes for large-scale climate models. In this case study, we used surface spectral reflectance data from satellite remote sensing to characterize spatial and temporal changes in vegetation and associated surface parameters in an area of about 350 {times} 400 km covering the southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site of the US Department of Energy`s Atmospheric Radiation Measurement (ARM) Program.« less

A multitemporal (1979-2009) land-use/land-cover dataset of the binational Santa Cruz Watershed

USGS Publications Warehouse

2011-01-01

Trends derived from multitemporal land-cover data can be used to make informed land management decisions and to help managers model future change scenarios. We developed a multitemporal land-use/land-cover dataset for the binational Santa Cruz watershed of southern Arizona, United States, and northern Sonora, Mexico by creating a series of land-cover maps at decadal intervals (1979, 1989, 1999, and 2009) using Landsat Multispectral Scanner and Thematic Mapper data and a classification and regression tree classifier. The classification model exploited phenological changes of different land-cover spectral signatures through the use of biseasonal imagery collected during the (dry) early summer and (wet) late summer following rains from the North American monsoon. Landsat images were corrected to remove atmospheric influences, and the data were converted from raw digital numbers to surface reflectance values. The 14-class land-cover classification scheme is based on the 2001 National Land Cover Database with a focus on "Developed" land-use classes and riverine "Forest" and "Wetlands" cover classes required for specific watershed models. The classification procedure included the creation of several image-derived and topographic variables, including digital elevation model derivatives, image variance, and multitemporal Kauth-Thomas transformations. The accuracy of the land-cover maps was assessed using a random-stratified sampling design, reference aerial photography, and digital imagery. This showed high accuracy results, with kappa values (the statistical measure of agreement between map and reference data) ranging from 0.80 to 0.85.

Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS)

NASA Astrophysics Data System (ADS)

Turner, Andrew; Bhat, Gs; Evans, Jonathan; Marsham, John; Martin, Gill; Parker, Douglas; Taylor, Chris; Bhattacharya, Bimal; Madan, Ranju; Mitra, Ashis; Mrudula, Gm; Muddu, Sekhar; Pattnaik, Sandeep; Rajagopal, En; Tripathi, Sachida

2015-04-01

The monsoon supplies the majority of water in South Asia, making understanding and predicting its rainfall vital for the growing population and economy. However, modelling and forecasting the monsoon from days to the season ahead is limited by large model errors that develop quickly, with significant inter-model differences pointing to errors in physical parametrizations such as convection, the boundary layer and land surface. These errors persist into climate projections and many of these errors persist even when increasing resolution. At the same time, a lack of detailed observations is preventing a more thorough understanding of monsoon circulation and its interaction with the land surface: a process governed by the boundary layer and convective cloud dynamics. The INCOMPASS project will support and develop modelling capability in Indo-UK monsoon research, including test development of a new Met Office Unified Model 100m-resolution domain over India. The first UK detachment of the FAAM research aircraft to India, in combination with an intensive ground-based observation campaign, will gather new observations of the surface, boundary layer structure and atmospheric profiles to go with detailed information on the timing of monsoon rainfall. Observations will be focused on transects in the northern plains of India (covering a range of surface types from irrigated to rain-fed agriculture, and wet to dry climatic zones) and across the Western Ghats and rain shadow in southern India (including transitions from land to ocean and across orography). A pilot observational campaign is planned for summer 2015, with the main field campaign to take place during spring/summer 2016. This project will advance our ability to forecast the monsoon, through a programme of measurements and modelling that aims to capture the key surface-atmosphere feedback processes in models. The observational analysis will allow a unique and unprecedented characterization of monsoon processes that will feed directly into model development at the UK Met Office and Indian NCMRWF, through model evaluation at a range of scales and leading to model improvement by working directly with parametrization developers. The project will institute a new long-term series of measurements of land surface fluxes, a particularly unconstrained observation for India, through eddy covariance flux towers. Combined with detailed land surface modelling using the Joint UK Land Environment Simulator (JULES) model, this will allow testing of land surface initialization in monsoon forecasts and improved land-atmosphere coupling.

Monitoring and validating spatio-temporal continuously daily evapotranspiration and its components at river basin scale

NASA Astrophysics Data System (ADS)

Song, L.; Liu, S.; Kustas, W. P.; Nieto, H.

2017-12-01

Operational estimation of spatio-temporal continuously daily evapotranspiration (ET), and the components evaporation (E) and transpiration (T), at watershed scale is very useful for developing a sustainable water resource strategy in semi-arid and arid areas. In this study, multi-year all-weather daily ET, E and T were estimated using MODIS-based (Dual Temperature Difference) DTD model under different land covers in Heihe watershed, China. The remotely sensed ET was validated using ground measurements from large aperture scintillometer systems, with a source area of several kilometers, under grassland, cropland and riparian shrub-forest. The results showed that the remotely sensed ET produced mean absolute percent deviation (MAPD) errors of about 30% during the growing season for all-weather conditions, but the model performed better under clear sky conditions. However, uncertainty in interpolated MODIS land surface temperature input data under cloudy conditions to the DTD model, and the representativeness of LAS measurements for the heterogeneous land surfaces contribute to the discrepancies between the modeled and ground measured surface heat fluxes, especially for the more humid grassland and heterogeneous shrub-forest sites.

The Goddard Snow Radiance Assimilation Project: An Integrated Snow Radiance and Snow Physics Modeling Framework for Snow/cold Land Surface Modeling

NASA Technical Reports Server (NTRS)

Kim, E.; Tedesco, M.; Reichle, R.; Choudhury, B.; Peters-Lidard C.; Foster, J.; Hall, D.; Riggs, G.

2006-01-01

Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.

Retinex at 50: color theory and spatial algorithms, a review

NASA Astrophysics Data System (ADS)

McCann, John J.

2017-05-01

Retinex Imaging shares two distinct elements: first, a model of human color vision; second, a spatial-imaging algorithm for making better reproductions. Edwin Land's 1964 Retinex Color Theory began as a model of human color vision of real complex scenes. He designed many experiments, such as Color Mondrians, to understand why retinal cone quanta catch fails to predict color constancy. Land's Retinex model used three spatial channels (L, M, S) that calculated three independent sets of monochromatic lightnesses. Land and McCann's lightness model used spatial comparisons followed by spatial integration across the scene. The parameters of their model were derived from extensive observer data. This work was the beginning of the second Retinex element, namely, using models of spatial vision to guide image reproduction algorithms. Today, there are many different Retinex algorithms. This special section, "Retinex at 50," describes a wide variety of them, along with their different goals, and ground truths used to measure their success. This paper reviews (and provides links to) the original Retinex experiments and image-processing implementations. Observer matches (measuring appearances) have extended our understanding of how human spatial vision works. This paper describes a collection very challenging datasets, accumulated by Land and McCann, for testing algorithms that predict appearance.

Hydrogeology and simulation of ground-water flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system, Texas

USGS Publications Warehouse

Kasmarek, Mark C.; Robinson, James L.

2004-01-01

As a part of the Texas Water Development Board Ground- Water Availability Modeling program, the U.S. Geological Survey developed and tested a numerical finite-difference (MODFLOW) model to simulate ground-water flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system in Texas from predevelopment (before 1891) through 2000. The model is intended to be a tool that water-resource managers can use to address future ground-water-availability issues.From land surface downward, the Chicot aquifer, the Evangeline aquifer, the Burkeville confining unit, the Jasper aquifer, and the Catahoula confining unit are the hydrogeologic units of the Gulf Coast aquifer system. Withdrawals of large quantities of ground water have resulted in potentiometric surface (head) declines in the Chicot, Evangeline, and Jasper aquifers and land-surface subsidence (primarily in the Houston area) from depressurization and compaction of clay layers interbedded in the aquifer sediments. In a generalized conceptual model of the aquifer system, water enters the ground-waterflow system in topographically high outcrops of the hydrogeologic units in the northwestern part of the approximately 25,000-square-mile model area. Water that does not discharge to streams flows to intermediate and deep zones of the system southeastward of the outcrop areas where it is discharged by wells and by upward leakage in topographically low areas near the coast. The uppermost parts of the aquifer system, which include outcrop areas, are under water-table conditions. As depth increases in the aquifer system and as interbedded sand and clay accumulate, water-table conditions evolve into confined conditions.The model comprises four layers, one for each of the hydrogeologic units of the aquifer system except the Catahoula confining unit, the assumed no-flow base of the system. Each layer consists of 137 rows and 245 columns of uniformly spaced grid blocks, each block representing 1 square mile. Lateral no-flow boundaries were located on the basis of outcrop extent (northwestern), major streams (southwestern, northeastern), and downdip limit of freshwater (southeastern). The MODFLOW general-head boundary package was used to simulate recharge and discharge in the outcrops of the hydrogeologic units. Simulation of land-surface subsidence (actually, compaction of clays) and release of water from storage in the clays of the Chicot and Evangeline aquifers was accomplished using the Interbed-Storage Package designed for use with the MODFLOW model. The model was calibrated by trial-anderror adjustment of selected model input data in a series of transient simulations until the model output (potentiometric surfaces, land-surface subsidence, and selected water-budget components) reasonably reproduced field measured (or estimated) aquifer responses.Model calibration comprised four elements: The first was qualitative comparison of simulated and measured heads in the aquifers for 1977 and 2000; and quantitative comparison by computation and areal distribution of the root-mean-square error between simulated and measured heads. The second calibration element was comparison of simulated and measured hydrographs from wells in the aquifers in a number of counties throughout the modeled area. The third calibration element was comparison of simulated water-budget componentsprimarily recharge and dischargeto estimates of physically reasonable ranges of actual water-budget components. The fourth calibration element was comparison of simulated land-surface subsidence from predevelopment to 2000 to measured land surface subsidence from 1906 through 1995.

Estimation of Regional Net CO2 Exchange over the Southern Great Plains

NASA Astrophysics Data System (ADS)

Biraud, S. C.; Riley, W. J.; Fischer, M. L.; Torn, M. S.; Cooley, H. S.

2004-12-01

Estimating spatially distributed ecosystem CO2 exchange is an important component of the North American Carbon Program. We describe here a methodology to estimate Net Ecosystem Exchange (NEE) over the Southern Great Plains, using: (1) data from the Department Of Energy's Atmospheric Radiation Measurement (ARM) sites in Oklahoma and Kansas; (2) meteorological forcing data from the Mesonet facilities; (3) soil and vegetation types from 1 km resolution USGS databases; (4) vegetation status (e.g., LAI) from 1 km satellite measurements of surface reflectance (MODIS); (5) a tested land-surface model; and (6) a coupled land-surface and meteorological model (MM5/ISOLSM). This framework allows us to simulate regional surface fluxes in addition to ABL and free troposphere concentrations of CO2 at a continental scale with fine-scale nested grids centered on the ARM central facility. We use the offline land-surface and coupled models to estimate regional NEE, and compare predictions to measurements from the 9 Extended Facility sites with eddy correlation measurements. Site level comparisons to portable ECOR measurements in several crop types are also presented. Our approach also allows us to extend bottom-up estimates to periods and areas where meteorological forcing data are unavailable.

Observed Variation in Carbon and Water Exchange Across Crop Types, Seasons, and Years in Un-irrigated Land of the Southern Great Plains

NASA Astrophysics Data System (ADS)

Fischer, M. L.; Billesbach, D. P.; Riley, W. J.; Berry, J. A.; Torn, M. S.

2004-12-01

Accurate prediction of the regional responses of carbon and water fluxes to changing climate, land use, and management requires models that are parameterized and tested against measurements made in multiple land cover types and over seasonal and inter-annual time scales. In particular, modelers predicting fluxes for un-irrigated agriculture are posed with the additional challenge of characterizing the onset and severity of water stress. We report results from three years of an ongoing series of measurement campaigns that quantify the spatial heterogeneity of land surface-atmosphere exchanges of carbon dioxide, water, and energy. Eddy covariance flux measurements were made in pastures and dominant crop types surrounding the US-DOE Atmospheric Radiation Measurement Program central facility near Lamont, Oklahoma (36.605 N, 97.485 W). Ancillary measurements included radiation budget, meteorology, soil moisture and temperature, leaf area index, plant biomass, and plant and soil carbon and nitrogen content. Within a given year, the dominant spatial variation in fluxes of carbon, water, and energy are caused by variations of land cover due to the distinct phenology of winter-spring (winter wheat) versus summer crops (e.g., pasture, sorghum, soybeans). Within crop and yearly variations were smaller. In 2002, variations in net ecosystem carbon exchange (NEE), for three closely spaced winter wheat fields was 10-20%. Variations between years for the same crop types were also large. Net primary production (NPP) of winter wheat in the spring of 2003 versus 2002 increased by a factor of two, while NEE increased by 35%. The large increase in production and NEE are positively correlated with precipitation, integrated over the previous summer-fall periods. We discuss the implications of these results by extracting and comparing factors relevant for parameterization of land surface models and by comparing crop yield with historic variations in yield at the landscape scale.

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

NASA Astrophysics Data System (ADS)

Saeki, Tazu; Patra, Prabir K.

2017-12-01

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

Vertical Landing Aerodynamics of Reusable Rocket Vehicle

NASA Astrophysics Data System (ADS)

Nonaka, Satoshi; Nishida, Hiroyuki; Kato, Hiroyuki; Ogawa, Hiroyuki; Inatani, Yoshifumi

The aerodynamic characteristics of a vertical landing rocket are affected by its engine plume in the landing phase. The influences of interaction of the engine plume with the freestream around the vehicle on the aerodynamic characteristics are studied experimentally aiming to realize safe landing of the vertical landing rocket. The aerodynamic forces and surface pressure distributions are measured using a scaled model of a reusable rocket vehicle in low-speed wind tunnels. The flow field around the vehicle model is visualized using the particle image velocimetry (PIV) method. Results show that the aerodynamic characteristics, such as the drag force and pitching moment, are strongly affected by the change in the base pressure distributions and reattachment of a separation flow around the vehicle.

Effects of Land-Use Changes and Ground-Water Withdrawals on Stream Base Flow, Pocono Creek Watershed, Monroe County, Pennsylvania

USGS Publications Warehouse

Sloto, Ronald A.

2008-01-01

The Pocono Creek watershed drains 46.5 square miles in eastern Monroe County, Pa. Between 2000 and 2020, the population of Monroe County is expected to increase by 70 percent, which will result in substantial changes in land-use patterns. An evaluation of the effect of reduced recharge from land-use changes and additional ground-water withdrawals on stream base flow was done by the U.S. Geological Survey (USGS) in cooperation with the U.S. Environmental Protection Agency (USEPA) and the Delaware River Basin Commission as part of the USEPA?s Framework for Sustainable Watershed Management Initiative. Two models were used. A Soil and Water Assessment Tool (SWAT) model developed by the USEPA provided areal recharge values for 2000 land use and projected full buildout land use. The USGS MODFLOW-2000 ground-water-flow model was used to estimate the effect of reduced recharge from changes in land use and additional ground-water withdrawals on stream base flow. This report describes the ground-water-flow-model simulations. The Pocono Creek watershed is underlain by sedimentary rock of Devonian age, which is overlain by a veneer of glacial deposits. All water-supply wells are cased into and derive water from the bedrock. In the ground-water-flow model, the surficial geologic units were grouped into six categories: (1) moraine deposits, (2) stratified drift, (3) lake deposits, (4) outwash, (5) swamp deposits, and (6) undifferentiated deposits. The unconsolidated surficial deposits are not used as a source of water. The ground-water and surface-water systems are well connected in the Pocono Creek watershed. Base flow measured on October 13, 2004, at 27 sites for model calibration showed that streams gained water between all sites measured except in the lower reach of Pocono Creek. The ground-water-flow model included the entire Pocono Creek watershed. Horizontally, the modeled area was divided into a 53 by 155 cell grid with 6,060 active cells. Vertically, the modeled area was discretized into four layers. Layers 1 and 2 represented the unconsolidated surficial deposits where they are present and bedrock where the surficial deposits are absent. Layer 3 represented shallow bedrock and was 200 ft (feet) thick. Layer 4 represented deep bedrock and was 300 ft thick. A total of 873 cells representing streams were assigned to layer 1. Recharge rates for model calibration were provided by the USEPA SWAT model for 2000 land-use conditions. Recharge rates for 2000 for the 29 subwatersheds in the SWAT model ranged from 6.11 to 22.66 inches per year. Because the ground-water-flow model was calibrated to base-flow data collected on October 13, 2004, the 2000 recharge rates were multiplied by 1.18 so the volume of recharge was equal to the volume of streamflow measured at the mouth of Pocono Creek. During model calibration, adjustments were made to aquifer hydraulic conductivity and streambed conductance. Simulated base flows and hydraulic heads were compared to measured base flows and hydraulic heads using the root mean squared error (RMSE) between measured and simulated values. The RMSE of the calibrated model for base flow was 4.7 cubic feet per second for 27 locations, and the RMSE for hydraulic heads for 15 locations was 35 ft. The USEPA SWAT model was used to provide areal recharge values for 2000 and full buildout land-use conditions. The change in recharge ranged from an increase of 37.8 percent to a decrease of 60.8 percent. The ground-water-flow model was used to simulate base flow for 2000 and full buildout land-use conditions using steady-state simulations. The decrease in simulated base flow ranged from 3.8 to 63 percent at the streamflow-measurement sites. Simulated base flow at streamflow-gaging station Pocono Creek above Wigwam Run near Stroudsburg, Pa. (01441495), decreased 25 percent. This is in general agreement with the SWAT model, which estimated a 30.6-percent loss in base flow at the streamflow-gaging station.

Modeling forest site productivity using mapped geospatial attributes within a South Carolina Landscape, USA

DOE PAGES

Parresol, B. R.; Scott, D. A.; Zarnoch, S. J.; ...

2017-12-15

Spatially explicit mapping of forest productivity is important to assess many forest management alternatives. We assessed the relationship between mapped variables and site index of forests ranging from southern pine plantations to natural hardwoods on a 74,000-ha landscape in South Carolina, USA. Mapped features used in the analysis were soil association, land use condition in 1951, depth to groundwater, slope and aspect. Basal area, species composition, age and height were the tree variables measured. Linear modelling identified that plot basal area, depth to groundwater, soils association and the interactions between depth to groundwater and forest group, and between land usemore » in 1951 and forest group were related to site index (SI) (R 2 =0.37), but this model had regression attenuation. We then used structural equation modeling to incorporate error-in-measurement corrections for basal area and groundwater to remove bias in the model. We validated this model using 89 independent observations and found the 95% confidence intervals for the slope and intercept of an observed vs. predicted site index error-corrected regression included zero and one, respectively, indicating a good fit. With error in measurement incorporated, only basal area, soil association, and the interaction between forest groups and land use were important predictors (R2 =0.57). Thus, we were able to develop an unbiased model of SI that could be applied to create a spatially explicit map based primarily on soils as modified by past (land use and forest type) and recent forest management (basal area).« less

Modeling forest site productivity using mapped geospatial attributes within a South Carolina Landscape, USA

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

Parresol, B. R.; Scott, D. A.; Zarnoch, S. J.

Spatially explicit mapping of forest productivity is important to assess many forest management alternatives. We assessed the relationship between mapped variables and site index of forests ranging from southern pine plantations to natural hardwoods on a 74,000-ha landscape in South Carolina, USA. Mapped features used in the analysis were soil association, land use condition in 1951, depth to groundwater, slope and aspect. Basal area, species composition, age and height were the tree variables measured. Linear modelling identified that plot basal area, depth to groundwater, soils association and the interactions between depth to groundwater and forest group, and between land usemore » in 1951 and forest group were related to site index (SI) (R 2 =0.37), but this model had regression attenuation. We then used structural equation modeling to incorporate error-in-measurement corrections for basal area and groundwater to remove bias in the model. We validated this model using 89 independent observations and found the 95% confidence intervals for the slope and intercept of an observed vs. predicted site index error-corrected regression included zero and one, respectively, indicating a good fit. With error in measurement incorporated, only basal area, soil association, and the interaction between forest groups and land use were important predictors (R2 =0.57). Thus, we were able to develop an unbiased model of SI that could be applied to create a spatially explicit map based primarily on soils as modified by past (land use and forest type) and recent forest management (basal area).« less

Improving simulated long-term responses of vegetation to temperature and precipitation extremes using the ACME land model

NASA Astrophysics Data System (ADS)

Ricciuto, D. M.; Warren, J.; Guha, A.

2017-12-01

While carbon and energy fluxes in current Earth system models generally have reasonable instantaneous responses to extreme temperature and precipitation events, they often do not adequately represent the long-term impacts of these events. For example, simulated net primary productivity (NPP) may decrease during an extreme heat wave or drought, but may recover rapidly to pre-event levels following the conclusion of the extreme event. However, field measurements indicate that long-lasting damage to leaves and other plant components often occur, potentially affecting the carbon and energy balance for months after the extreme event. The duration and frequency of such extreme conditions is likely to shift in the future, and therefore it is critical for Earth system models to better represent these processes for more accurate predictions of future vegetation productivity and land-atmosphere feedbacks. Here we modify the structure of the Accelerated Climate Model for Energy (ACME) land surface model to represent long-term impacts and test the improved model against observations from experiments that applied extreme conditions in growth chambers. Additionally, we test the model against eddy covariance measurements that followed extreme conditions at selected locations in North America, and against satellite-measured vegetation indices following regional extreme events.

Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Kumar, Sujay; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Zhou, Shuija

2012-01-01

Land-atmosphere (L-A) Interactions playa critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (US-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF Simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

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

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

Real Time Land-Surface Hydrologic Modeling Over Continental US

NASA Technical Reports Server (NTRS)

Houser, Paul R.

1998-01-01

The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

Assimilation of Satellite-Derived Skin Temperature Observations into Land Surface Models

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Kumar, Sujay V.; Mahanama, P. P.; Koster, Randal D.; Liu, Q.

2010-01-01

Land surface (or "skin") temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. Here we assimilate LST retrievals from the International Satellite Cloud Climatology Project (ISCCP) into the Noah and Catchment (CLSM) land surface models using an ensemble-based, off-line land data assimilation system. LST is described very differently in the two models. A priori scaling and dynamic bias estimation approaches are applied because satellite and model LST typically exhibit different mean values and variability. Performance is measured against 27 months of in situ measurements from the Coordinated Energy and Water Cycle Observations Project at 48 stations. LST estimates from Noah and CLSM without data assimilation ("open loop") are comparable to each other and superior to that of ISCCP retrievals. For LST, RMSE values are 4.9 K (CLSM), 5.6 K (Noah), and 7.6 K (ISCCP), and anomaly correlation coefficients (R) are 0.62 (CLSM), 0.61 (Noah), and 0.52 (ISCCP). Assimilation of ISCCP retrievals provides modest yet statistically significant improvements (over open loop) of up to 0.7 K in RMSE and 0.05 in anomaly R. The skill of surface turbulent flux estimates from the assimilation integrations is essentially identical to the corresponding open loop skill. Noah assimilation estimates of ground heat flux, however, can be significantly worse than open loop estimates. Provided the assimilation system is properly adapted to each land model, the benefits from the assimilation of LST retrievals are comparable for both models.

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

PubMed

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

2016-03-01

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

Was There a Significantly Negative Anomaly of Global Land Surface Net Radiation from 2001-2006?

NASA Astrophysics Data System (ADS)

Liang, S.; Jia, A.; Jiang, B.

2016-12-01

Surface net radiation, which characterizes surface energy budget, can be estimated from in-situ measurements, satellite products, model simulations, and reanalysis. Satellite products are usually validated using ground measurements to characterize their uncertainties. The surface net radiation product from the CERES (Clouds and the Earth's Radiant Energy System) has been widely used. After validating it using extensive ground measurements, we also verified that the CERES surface net radiation product is highly accurate. When we evaluated the temporal variations of the averaged global land surface net radiation from the CERES product, we found a significantly negative anomaly starting from 2001, reaching the maximum in 2004, and gradually coming back to normal in 2006. The valley has the magnitude of approximately 3 Wm-2 centered at 2004. After comparing with the high-resolution GLASS (Global LAnd Surface Satellite) net radiation product developed at Beijing Normal University, the CMIP5 model simulations, and the ERA-Interim reanalysis dataset, we concluded that the significant decreasing pattern of land surface net radiation from 2001-2006 is an artifact mainly due to inaccurate longwave net radiation of the CERES surface net radiation product. The current ground measurement networks are not spatially dense enough to capture the false negative anomaly from the CERES product, which calls for more ground measurements.

Population stress: A spatiotemporal analysis of population change and land development at the county level in the contiguous United States, 2001-2011.

PubMed

Chi, Guangqing; Ho, Hung Chak

2018-01-01

The past century has witnessed rapidly increasing population-land conflicts due to exponential population growth and its many consequences. Although the measures of population-land conflicts are many, there lacks a model that appropriately considers both the social and physical contexts of population-land conflicts. In this study we introduce the concept of population stress , which identifies areas with populations growing faster than the lands available for sustainable development. Specifically, population stress areas are identified by comparing population growth and land development as measured by land developability in the contiguous United States from 2001 to 2011. Our approach is based on a combination of spatial multicriteria analysis, zonal statistics, and spatiotemporal modeling. We found that the population growth of a county is associated with the decrease of land developability, along with the spatial influences of surrounding counties. The Midwest and the traditional "Deep South" counties would have less population stress with future land development, whereas the Southeast Coast, Washington State, Northern Texas, and the Southwest would face more stress due to population growth that is faster than the loss of suitable lands for development. The factors contributing to population stress may differ from place to place. Our population stress concept is useful and innovative for understanding population stress due to land development and can be applied to other regions as well as global research. It can act as a basis towards developing coherent sustainable land use policies. Coordination among local governments and across different levels of governments in the twenty-first century is a must for effective land use planning.

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

PubMed

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

2013-10-15

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

A digital spatial predictive model of land-use change using economic and environmental inputs and a statistical tree classification approach: Thailand, 1970s--1990s

NASA Astrophysics Data System (ADS)

Felkner, John Sames

The scale and extent of global land use change is massive, and has potentially powerful effects on the global climate and global atmospheric composition (Turner & Meyer, 1994). Because of this tremendous change and impact, there is an urgent need for quantitative, empirical models of land use change, especially predictive models with an ability to capture the trajectories of change (Agarwal, Green, Grove, Evans, & Schweik, 2000; Lambin et al., 1999). For this research, a spatial statistical predictive model of land use change was created and run in two provinces of Thailand. The model utilized an extensive spatial database, and used a classification tree approach for explanatory model creation and future land use (Breiman, Friedman, Olshen, & Stone, 1984). Eight input variables were used, and the trees were run on a dependent variable of land use change measured from 1979 to 1989 using classified satellite imagery. The derived tree models were used to create probability of change surfaces, and these were then used to create predicted land cover maps for 1999. These predicted 1999 maps were compared with actual 1999 landcover derived from 1999 Landsat 7 imagery. The primary research hypothesis was that an explanatory model using both economic and environmental input variables would better predict future land use change than would either a model using only economic variables or a model using only environmental. Thus, the eight input variables included four economic and four environmental variables. The results indicated a very slight superiority of the full models to predict future agricultural change and future deforestation, but a slight superiority of the economic models to predict future built change. However, the margins of superiority were too small to be statistically significant. The resulting tree structures were used, however, to derive a series of principles or "rules" governing land use change in both provinces. The model was able to predict future land use, given a series of assumptions, with 90 percent overall accuracies. The model can be used in other developing or developed country locations for future land use prediction, determination of future threatened areas, or to derive "rules" or principles driving land use change.

A Simplified Land Model (SLM) for use in cloud-resolving models: Formulation and evaluation

NASA Astrophysics Data System (ADS)

Lee, Jungmin M.; Khairoutdinov, Marat

2015-09-01

A Simplified Land Model (SLM) that uses a minimalist set of parameters with a single-layer vegetation and multilevel soil structure has been developed distinguishing canopy and undercanopy energy budgets. The primary motivation has been to design a land model for use in the System for Atmospheric Modeling (SAM) cloud-resolving model to study land-atmosphere interactions with a sufficient level of realism. SLM uses simplified expressions for the transport of heat, moisture, momentum, and radiation in soil-vegetation system. The SLM performance has been evaluated over several land surface types using summertime tower observations of micrometeorological and biophysical data from three AmeriFlux sites, which include grassland, cropland, and deciduous-broadleaf forest. In general, the SLM captures the observed diurnal cycle of surface energy budget and soil temperature reasonably well, although reproducing the evolution of soil moisture, especially after rain events, has been challenging. The SLM coupled to SAM has been applied to the case of summertime shallow cumulus convection over land based on the Atmospheric Radiation Measurements (ARM) Southern Great Plain (SGP) observations. The simulated surface latent and sensible heat fluxes as well as the evolution of thermodynamic profiles in convective boundary layer agree well with the estimates based on the observations. Sensitivity of atmospheric boundary layer development to the soil moisture and different land cover types has been also examined.

Effects of Land-use/Land-cover and Climate Changes on Water Quantity and Quality in Sub-basins near Major US Cities in the Great Lakes Region

NASA Astrophysics Data System (ADS)

Murphy, L.; Al-Hamdan, M. Z.; Crosson, W. L.; Barik, M.

2017-12-01

Land-cover change over time to urbanized, less permeable surfaces, leads to reduced water infiltration at the location of water input while simultaneously transporting sediments, nutrients and contaminants farther downstream. With an abundance of agricultural fields bordering the greater urban areas of Milwaukee, Detroit, and Chicago, water and nutrient transport is vital to the farming industry, wetlands, and communities that rely on water availability. Two USGS stream gages each located within a sub-basin near each of these Great Lakes Region cities were examined, one with primarily urban land-cover between 1992 and 2011, and one with primarily agriculture land-cover. ArcSWAT, a watershed model and soil and water assessment tool used in extension with ArcGIS, was used to develop hydrologic models that vary the land-covers to simulate surface runoff during a model run period from 2004 to 2008. Model inputs that include a digital elevation model (DEM), Landsat-derived land-use/land-cover (LULC) satellite images from 1992, 2001, and 2011, soil classification, and meteorological data were used to determine the effect of different land-covers on the water runoff, nutrients and sediments. The models were then calibrated and validated to USGS stream gage data measurements over time. Additionally, the watershed model was run based on meteorological data from an IPCC CMIP5 high emissions climate change scenario for 2050. Model outputs from the different LCLU scenarios were statistically evaluated and results showed that water runoff, nutrients and sediments were impacted by LULC change in four out of the six sub-basins. In the 2050 climate scenario, only one out of the six sub-basin's water quantity and quality was affected. These results contribute to the importance of developing hydrologic models as the dependence on the Great Lakes as a freshwater resource competes with the expansion of urbanization leading to the movement of runoff, nutrients, and sediments off the land.

Calculated and scale model experimentally measured scattering from metallic structures in Instrument Landing System

DOT National Transportation Integrated Search

1974-03-01

Comparison is made of theoretically calculated and experimentally determined scattering from metallic tilted rectangles and vertical cylindrical scatterers. The scattering was experimentally measured in a scale model range at the Watertown Arsenal, W...

The Atlanta Urban Heat Island Mitigation and Air Quality Modeling Project: How High-Resoution Remote Sensing Data Can Improve Air Quality Models

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William L.; Khan, Maudood N.

2006-01-01

The Atlanta Urban Heat Island and Air Quality Project had its genesis in Project ATLANTA (ATlanta Land use Analysis: Temperature and Air quality) that began in 1996. Project ATLANTA examined how high-spatial resolution thermal remote sensing data could be used to derive better measurements of the Urban Heat Island effect over Atlanta. We have explored how these thermal remote sensing, as well as other imaged datasets, can be used to better characterize the urban landscape for improved air quality modeling over the Atlanta area. For the air quality modeling project, the National Land Cover Dataset and the local scale Landpro99 dataset at 30m spatial resolutions have been used to derive land use/land cover characteristics for input into the MM5 mesoscale meteorological model that is one of the foundations for the Community Multiscale Air Quality (CMAQ) model to assess how these data can improve output from CMAQ. Additionally, land use changes to 2030 have been predicted using a Spatial Growth Model (SGM). SGM simulates growth around a region using population, employment and travel demand forecasts. Air quality modeling simulations were conducted using both current and future land cover. Meteorological modeling simulations indicate a 0.5 C increase in daily maximum air temperatures by 2030. Air quality modeling simulations show substantial differences in relative contributions of individual atmospheric pollutant constituents as a result of land cover change. Enhanced boundary layer mixing over the city tends to offset the increase in ozone concentration expected due to higher surface temperatures as a result of urbanization.

Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Maximization-Complementary Superiority (LCMCS) Method.

PubMed

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Xi, Xiuxiu

2015-07-23

The measurement of soil total nitrogen (TN) by hyperspectral remote sensing provides an important tool for soil restoration programs in areas with subsided land caused by the extraction of natural resources. This study used the local correlation maximization-complementary superiority method (LCMCS) to establish TN prediction models by considering the relationship between spectral reflectance (measured by an ASD FieldSpec 3 spectroradiometer) and TN based on spectral reflectance curves of soil samples collected from subsided land which is determined by synthetic aperture radar interferometry (InSAR) technology. Based on the 1655 selected effective bands of the optimal spectrum (OSP) of the first derivate differential of reciprocal logarithm ([log{1/R}]'), (correlation coefficients, p < 0.01), the optimal model of LCMCS method was obtained to determine the final model, which produced lower prediction errors (root mean square error of validation [RMSEV] = 0.89, mean relative error of validation [MREV] = 5.93%) when compared with models built by the local correlation maximization (LCM), complementary superiority (CS) and partial least squares regression (PLS) methods. The predictive effect of LCMCS model was optional in Cangzhou, Renqiu and Fengfeng District. Results indicate that the LCMCS method has great potential to monitor TN in subsided lands caused by the extraction of natural resources including groundwater, oil and coal.

The 'Geographic Emission Benchmark' model: a baseline approach to measuring emissions associated with deforestation and degradation.

PubMed

Kim, Oh Seok; Newell, Joshua P

2015-10-01

This paper proposes a new land-change model, the Geographic Emission Benchmark (GEB), as an approach to quantify land-cover changes associated with deforestation and forest degradation. The GEB is designed to determine 'baseline' activity data for reference levels. Unlike other models that forecast business-as-usual future deforestation, the GEB internally (1) characterizes 'forest' and 'deforestation' with minimal processing and ground-truthing and (2) identifies 'deforestation hotspots' using open-source spatial methods to estimate regional rates of deforestation. The GEB also characterizes forest degradation and identifies leakage belts. This paper compares the accuracy of GEB with GEOMOD, a popular land-change model used in the UN-REDD (Reducing Emissions from Deforestation and Forest Degradation) Program. Using a case study of the Chinese tropics for comparison, GEB's projection is more accurate than GEOMOD's, as measured by Figure of Merit. Thus, the GEB produces baseline activity data that are moderately accurate for the setting of reference levels.

Mars Exploration Rovers Landing Dispersion Analysis

NASA Technical Reports Server (NTRS)

Knocke, Philip C.; Wawrzyniak, Geoffrey G.; Kennedy, Brian M.; Desai, Prasun N.; Parker, TImothy J.; Golombek, Matthew P.; Duxbury, Thomas C.; Kass, David M.

2004-01-01

Landing dispersion estimates for the Mars Exploration Rover missions were key elements in the site targeting process and in the evaluation of landing risk. This paper addresses the process and results of the landing dispersion analyses performed for both Spirit and Opportunity. The several contributors to landing dispersions (navigation and atmospheric uncertainties, spacecraft modeling, winds, and margins) are discussed, as are the analysis tools used. JPL's MarsLS program, a MATLAB-based landing dispersion visualization and statistical analysis tool, was used to calculate the probability of landing within hazardous areas. By convolving this with the probability of landing within flight system limits (in-spec landing) for each hazard area, a single overall measure of landing risk was calculated for each landing ellipse. In-spec probability contours were also generated, allowing a more synoptic view of site risks, illustrating the sensitivity to changes in landing location, and quantifying the possible consequences of anomalies such as incomplete maneuvers. Data and products required to support these analyses are described, including the landing footprints calculated by NASA Langley's POST program and JPL's AEPL program, cartographically registered base maps and hazard maps, and flight system estimates of in-spec landing probabilities for each hazard terrain type. Various factors encountered during operations, including evolving navigation estimates and changing atmospheric models, are discussed and final landing points are compared with approach estimates.

Comparing evapotranspiration from Eddy covariance measurements, water budgets, remote sensing, and land surface models over Canada a, b

DOE PAGES

Wang, Shusen; Pan, Ming; Mu, Qiaozhen; ...

2015-07-29

Here, this study compares six evapotranspiration ET products for Canada's landmass, namely, eddy covariance EC measurements; surface water budget ET; remote sensing ET from MODIS; and land surface model (LSM) ET from the Community Land Model (CLM), the Ecological Assimilation of Land and Climate Observations (EALCO) model, and the Variable Infiltration Capacity model (VIC). The ET climatology over the Canadian landmass is characterized and the advantages and limitations of the datasets are discussed. The EC measurements have limited spatial coverage, making it difficult for model validations at the national scale. Water budget ET has the largest uncertainty because of datamore » quality issues with precipitation in mountainous regions and in the north. MODIS ET shows relatively large uncertainty in cold seasons and sparsely vegetated regions. The LSM products cover the entire landmass and exhibit small differences in ET among them. Annual ET from the LSMs ranges from small negative values to over 600 mm across the landmass, with a countrywide average of 256 ± 15 mm. Seasonally, the countrywide average monthly ET varies from a low of about 3 mm in four winter months (November-February) to 67 ± 7 mm in July. The ET uncertainty is scale dependent. Larger regions tend to have smaller uncertainties because of the offset of positive and negative biases within the region. More observation networks and better quality controls are critical to improving ET estimates. Future techniques should also consider a hybrid approach that integrates strengths of the various ET products to help reduce uncertainties in ET estimation.« less

Comparing evapotranspiration from Eddy covariance measurements, water budgets, remote sensing, and land surface models over Canada a, b

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

Wang, Shusen; Pan, Ming; Mu, Qiaozhen

Here, this study compares six evapotranspiration ET products for Canada's landmass, namely, eddy covariance EC measurements; surface water budget ET; remote sensing ET from MODIS; and land surface model (LSM) ET from the Community Land Model (CLM), the Ecological Assimilation of Land and Climate Observations (EALCO) model, and the Variable Infiltration Capacity model (VIC). The ET climatology over the Canadian landmass is characterized and the advantages and limitations of the datasets are discussed. The EC measurements have limited spatial coverage, making it difficult for model validations at the national scale. Water budget ET has the largest uncertainty because of datamore » quality issues with precipitation in mountainous regions and in the north. MODIS ET shows relatively large uncertainty in cold seasons and sparsely vegetated regions. The LSM products cover the entire landmass and exhibit small differences in ET among them. Annual ET from the LSMs ranges from small negative values to over 600 mm across the landmass, with a countrywide average of 256 ± 15 mm. Seasonally, the countrywide average monthly ET varies from a low of about 3 mm in four winter months (November-February) to 67 ± 7 mm in July. The ET uncertainty is scale dependent. Larger regions tend to have smaller uncertainties because of the offset of positive and negative biases within the region. More observation networks and better quality controls are critical to improving ET estimates. Future techniques should also consider a hybrid approach that integrates strengths of the various ET products to help reduce uncertainties in ET estimation.« less

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.

Developing Conceptual Models for Assessing Climate Change Impacts to Contaminant Availability in Terrestrial Ecosystems

DTIC Science & Technology

2015-03-01

Stressors Secondary Source/ Stressors Measures of Effect Score Summary Individual Scores Compile Results Land Management (e.g., controlled fire ...Secondary Source/ Stressors Measures of Effect Score Summary Individual Scores Compile Results Land Management (e.g., controlled fire , timber...Greenberg 2005), effects of dredged material (PIANC 2006), and ecosystem restoration (Fischenich 2008) among others. The process of developing a conceptual

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

USGS Publications Warehouse

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

2014-01-01

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

Likelihood parameter estimation for calibrating a soil moisture using radar backscatter

USDA-ARS?s Scientific Manuscript database

Assimilating soil moisture information contained in synthetic aperture radar imagery into land surface model predictions can be done using a calibration, or parameter estimation, approach. The presence of speckle, however, necessitates aggregating backscatter measurements over large land areas in or...

Impact of Calibrated Land Surface Model Parameters on the Accuracy and Uncertainty of Land-Atmosphere Coupling in WRF Simulations

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (LIS-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also 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.

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.

Acoustic Measurements of a Large Civil Transport Main Landing Gear Model

NASA Technical Reports Server (NTRS)

Ravetta, Patricio A.; Khorrami, Mehdi R.; Burdisso, Ricardo A.; Wisda, David M.

2016-01-01

Microphone phased array acoustic measurements of a 26 percent-scale, Boeing 777-200 main landing gear model with and without noise reduction fairings installed were obtained in the anechoic configuration of the Virginia Tech Stability Tunnel. Data were acquired at Mach numbers of 0.12, 0.15, and 0.17 with the latter speed used as the nominal test condition. The fully and partially dressed gear with the truck angle set at 13 degrees toe-up landing configuration were the two most extensively tested configurations, serving as the baselines for comparison purposes. Acoustic measurements were also acquired for the same two baseline configurations with the truck angle set at 0 degrees. In addition, a previously tested noise reducing, toboggan-shaped fairing was re-evaluated extensively to address some of the lingering questions regarding the extent of acoustic benefit achievable with this device. The integrated spectra generated from the acoustic source maps reconfirm, in general terms, the previously reported noise reduction performance of the toboggan fairing as installed on an isolated gear. With the recent improvements to the Virginia Tech tunnel acoustic quality and microphone array capabilities, the present measurements provide an additional, higher quality database to the acoustic information available for this gear model.

Toward an Improved Understanding of the Global Fresh Water Budget

NASA Technical Reports Server (NTRS)

Hildebrand, Peter H.

2005-01-01

The major components of the global fresh water cycle include the evaporation from the land and ocean surfaces, precipitation onto the Ocean and land surfaces, the net atmospheric transport of water from oceanic areas over land, and the return flow of water from the land back into the ocean. The additional components of oceanic water transport are few, principally, the mixing of fresh water through the oceanic boundary layer, transport by ocean currents, and sea ice processes. On land the situation is considerably more complex, and includes the deposition of rain and snow on land; water flow in runoff; infiltration of water into the soil and groundwater; storage of water in soil, lakes and streams, and groundwater; polar and glacial ice; and use of water in vegetation and human activities. Knowledge of the key terms in the fresh water flux budget is poor. Some components of the budget, e.g. precipitation, runoff, storage, are measured with variable accuracy across the globe. We are just now obtaining precise measurements of the major components of global fresh water storage in global ice and ground water. The easily accessible fresh water sources in rivers, lakes and snow runoff are only adequately measured in the more affluent portions of the world. presents proposals are suggesting methods of making global measurements of these quantities from space. At the same time, knowledge of the global fresh water resources under the effects of climate change is of increasing importance and the human population grows. This paper provides an overview of the state of knowledge of the global fresh water budget, evaluating the accuracy of various global water budget measuring and modeling techniques. We review the measurement capabilities of satellite instruments as compared with field validation studies and modeling approaches. Based on these analyses, and on the goal of improved knowledge of the global fresh water budget under the effects of climate change, we suggest priorities for future improvements in global fresh water budget monitoring. The priorities are based on the potential of new approaches to provide improved measurement and modeling systems, and on the need to measure and understand the potential for a speed-up of the global water cycle under the effects of climate change.

Simulation, guidance and navigation of the B-737 for rollout and turnoff using MLS measurements

NASA Technical Reports Server (NTRS)

Pines, S.; Schmidt, S. F.; Mann, F.

1975-01-01

A simulation program is described for the B-737 aircraft in landing approach, a touchdown, rollout and turnoff for normal and CAT III weather conditions. Preliminary results indicate that microwave landing systems can be used in place of instrument landing systems landing aids and that a single magnetic cable can be used for automated rollout and turnoff. Recommendations are made for further refinement of the model and additional testing to finalize a set of guidance laws for rollout and turnoff.

A Comparison of the Diel Cycle of Modeled and Measured Latent Heat Flux During the Warm Season in a Colorado Subalpine Forest

NASA Astrophysics Data System (ADS)

Burns, Sean P.; Swenson, Sean C.; Wieder, William R.; Lawrence, David M.; Bonan, Gordon B.; Knowles, John F.; Blanken, Peter D.

2018-03-01

Precipitation changes the physiological characteristics of an ecosystem. Because land-surface models are often used to project changes in the hydrological cycle, modeling the effect of precipitation on the latent heat flux λE is an important aspect of land-surface models. Here we contrast conditionally sampled diel composites of the eddy-covariance fluxes from the Niwot Ridge Subalpine Forest AmeriFlux tower with the Community Land Model (CLM, version 4.5). With respect to measured λE during the warm season: for the day following above-average precipitation, λE was enhanced at midday by ≈40 W m-2 (relative to dry conditions), and nocturnal λE increased from ≈10 W m-2 in dry conditions to over 20 W m-2 in wet conditions. With default settings, CLM4.5 did not successfully model these changes. By increasing the amount of time that rainwater was retained by the canopy/needles, CLM was able to match the observed midday increase in λE on a dry day following a wet day. Stable nighttime conditions were problematic for CLM4.5. Nocturnal CLM λE had only a small (≈3 W m-2) increase during wet conditions, CLM nocturnal friction velocity u∗ was smaller than observed u∗, and CLM canopy air temperature was 2°C less than those measured at the site. Using observed u∗ as input to CLM increased λE; however, this caused CLM λE to be increased during both wet and dry periods. We suggest that sloped topography and the ever-present drainage flow enhanced nocturnal u∗ and λE. Such phenomena would not be properly captured by topographically blind land-surface models, such as CLM.

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.

Characterizations of pumping-induced land subsidence in coastal aquifers - model development and field-scale implementations

NASA Astrophysics Data System (ADS)

Ni, C.; Huang, Y.; Lu, C.

2012-12-01

The pumping-induced land subsidence events are typically founded in coastal aquifers in Taiwan especially in the areas of lower alluvial fans. Previous investigations have recognized the irreversible situation for an aquifer deformation even if the pumped water is significantly reduced or stopped. Long-term monitoring projects on land subsidence in Choshui alluvial fan in central Taiwan have improved the understanding of the deformations in the aquifer system. To characterization the detailed land subsidence mechanism, this study develops an inverse numerical model to estimate the deformation parameters such as the specific storage (Ss) and vertical hydraulic conductivity (Kv) for interbeds. Similar to the concept of Hydraulic tomography survey (HTS), the developed model employs the iterative cokriging estimator to improve the accuracy of estimating deformation parameters. A one-dimensional numerical example is employed to assess the accuracy of the developed inverse model. The developed model is then applied to field-scale data from compaction monitoring wells (CMW) installed in the lower Choshui River fan. Results of the synthetic example show that the developed inverse model can reproduce well the predefined geologic features of the synthetic aquifer. The model provides better estimations of Kv patterns and magnitudes. Slightly less detail of the Ss was obtained due to the insensitivity of transient stresses for specified sampling times. Without prior information from field measurements, the developed model associated with deformation measurements form CMW can estimate Kv and Ss fields with great spatial resolution.

"Detecting people"

NASA Astrophysics Data System (ADS)

Arneth, A.; Pugh, T.; Krause, A.; Bayer, A.; Lindeskog, M.

2015-12-01

Land-use change (LUC) is known to significantly affect biogeochemical cycles as well as surface energy partitioning - with important implications, ranging from understanding present-day measurements, to simulations of climate change and impacts on ecosystems, to assessments of the mitigation potential of land-based mitigation policies on ecosystems. When connecting observations of surface-atmosphere interactions and modelling at different scales, two important issues in this context are: legacy effects (e.g., to what degree and for how long does past LUC at a given location affect vegetation structure, CO2 fluxes and carbon pools), and sub-grid variability of the land-use change per se (e.g., whether bi-directional information about changes are taken into consideration). Both are important when bridging between scales (in time and in space) to enhance long-term observation networks. This contribution to the session will be very much from a process-based modelling perspective. Using a second generation dynamic global vegetation model we will show how different land-use histories impact vegetation and soil recovery (carbon pool-size, fluxes) differently, depending on the type of previous land-use, its length, and on the type of biome. We also study the difference between "gross" and "net" LUC accounting for simulated carbon cycling. Two important aspects, considering the session's objectives, are: 1) When establishing and developing observation networks, land-use history is key information for the interpretation of measured fluxes and needs to be collected and made available;, 2) Observation networks that "operate" solely in the natural science domain need to increasingly seek cooperation with socio-economic observations (such as land-use change, land management) in order to gain better understanding of coupled socio-ecological systems.

Modeling effects of traffic and landscape characteristics on ambient nitrogen dioxide levels in Connecticut

NASA Astrophysics Data System (ADS)

Skene, Katherine J.; Gent, Janneane F.; McKay, Lisa A.; Belanger, Kathleen; Leaderer, Brian P.; Holford, Theodore R.

2010-12-01

An integrated exposure model was developed that estimates nitrogen dioxide (NO 2) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO 2 taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO 2 measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO 2 levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.

Sensitivity of land surface modeling to parameters: An uncertainty quantification method applied to the Community Land Model

NASA Astrophysics Data System (ADS)

Ricciuto, D. M.; Mei, R.; Mao, J.; Hoffman, F. M.; Kumar, J.

2015-12-01

Uncertainties in land parameters could have important impacts on simulated water and energy fluxes and land surface states, which will consequently affect atmospheric and biogeochemical processes. Therefore, quantification of such parameter uncertainties using a land surface model is the first step towards better understanding of predictive uncertainty in Earth system models. In this study, we applied a random-sampling, high-dimensional model representation (RS-HDMR) method to analyze the sensitivity of simulated photosynthesis, surface energy fluxes and surface hydrological components to selected land parameters in version 4.5 of the Community Land Model (CLM4.5). Because of the large computational expense of conducting ensembles of global gridded model simulations, we used the results of a previous cluster analysis to select one thousand representative land grid cells for simulation. Plant functional type (PFT)-specific uniform prior ranges for land parameters were determined using expert opinion and literature survey, and samples were generated with a quasi-Monte Carlo approach-Sobol sequence. Preliminary analysis of 1024 simulations suggested that four PFT-dependent parameters (including slope of the conductance-photosynthesis relationship, specific leaf area at canopy top, leaf C:N ratio and fraction of leaf N in RuBisco) are the dominant sensitive parameters for photosynthesis, surface energy and water fluxes across most PFTs, but with varying importance rankings. On the other hand, for surface ans sub-surface runoff, PFT-independent parameters, such as the depth-dependent decay factors for runoff, play more important roles than the previous four PFT-dependent parameters. Further analysis by conditioning the results on different seasons and years are being conducted to provide guidance on how climate variability and change might affect such sensitivity. This is the first step toward coupled simulations including biogeochemical processes, atmospheric processes or both to determine the full range of sensitivity of Earth system modeling to land-surface parameters. This can facilitate sampling strategies in measurement campaigns targeted at reduction of climate modeling uncertainties and can also provide guidance on land parameter calibration for simulation optimization.

Using ARM Observations to Evaluate Climate Model Representation of Land-Atmosphere Coupling on the U.S. Southern Great Plains

NASA Astrophysics Data System (ADS)

Phillips, T. J.; Klein, S. A.; Ma, H. Y.; Tang, Q.

2016-12-01

Statistically significant coupling between summertime soil moisture and various atmospheric variables has been observed at the U.S. Southern Great Plains (SGP) facilities maintained by the U.S. DOE Atmospheric Radiation Measurement (ARM) program (Phillips and Klein, 2014 JGR). In the current study, we employ several independent measurements of shallow-depth soil moisture (SM) and of the surface evaporative fraction (EF) over multiple summers in order to estimate the range of SM-EF coupling strength at seven sites, and to approximate the SGP regional-scale coupling strength (and its uncertainty). We will use this estimate of regional-scale SM-EF coupling strength to evaluate its representation in version 5.1 of the global Community Atmosphere Model (CAM5.1) coupled to the CLM4 Land Model. Two experimental cases are considered for the 2003-2011 study period: 1) an Atmospheric Model Intercomparison Project (AMIP) run with historically observed sea surface temperatures specified, and 2) a more constrained hindcast run in which the CAM5.1 atmospheric state is initialized each day from the ERA Interim reanalysis, while the CLM4 initial conditions are obtained from an offline run of the land model using observed surface net radiation, precipitation, and wind as forcings. These twin experimental cases allow a distinction to be drawn between the land-atmosphere coupling in the free-running CAM5.1/CLM4 model and that in which the land and atmospheric states are constrained to remain closer to "reality". The constrained hindcast case, for example, should allow model errors in coupling strength to be related more closely to potential deficiencies in land-surface or atmospheric boundary-layer parameterizations. AcknowledgmentsThis work was funded by the U.S. Department of Energy Office of Science and was performed at the Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

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.

Simulation of the Onset of the Southeast Asian Monsoon During 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lau, W.; Baker, R.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo-China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the low-level temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation. The model results will be compared to the simulation of the 6-7 May 2000 Missouri flash flood event. In addition, the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation will be examined.

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Wang, Y.; Lau, W.; Baker, R. D.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo-China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the low-level temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation. The model results will be compared to the simulation of the 6-7 May 2000 Missouri flash flood event. In addition, the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation will be examined.

Principles in Remote Sensing of Aerosol from MODIS Over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Chu, D. A.

1999-01-01

The well-calibrated spectral radiances measured by MODIS will be processed to retrieve daily aerosol properties that include optical thickness and mass loading over land and optical thickness, the mean particle size of the dominant mode and the ratio between aerosol modes over ocean. In addition, after launch, aerosol single scattering albedo will be calculated as an experimental product. The retrieval process over land is based on a dark target method that identifies appropriate targets in the mid-IR channels and uses an empirical relationship found between the mid-ER and the visible channels to estimate surface reflectance in the visible from the mid-HZ reflectance measured by satellite. The method employs new aerosol models for industrial, smoke and dust aerosol. The process for retrieving aerosol over the ocean makes use of the wide spectral band from 0.55-2.13 microns and a look-up table constructed from combinations of five accumulation modes and five coarse modes. Both the over land and over ocean algorithms have been validated with satellite and airborne radiance measurements. We estimate that MODIS will be able to measure aerosol optical thickness (t) to within 0.05 +/- 0.2t over land and to within 0.05 +/- 0.05t over ocean. Much of the earth's surface is located far from aerosol sources and experience very low aerosol optical thickness. Will the accuracy expected from MODIS retrievals be sufficient to measure the global aerosol direct and indirect forcing? We are attempting to answer this question using global model results and cloud climatology.

Defining, Measuring, and Incentivizing Sustainable Land Use to Meet Human Needs

NASA Astrophysics Data System (ADS)

Nicholas, K. A.; Brady, M. V.; Olin, S.; Ekroos, J.; Hall, M.; Seaquist, J. W.; Lehsten, V.; Smith, H.

2016-12-01

Land is a natural capital that supports the flow of an enormous amount of ecosystem services critical to human welfare. Sustainable land use, which we define as land use that meets both current and future human needs for ecosystem services, is essential to meet global goals for climate mitigation and sustainable development, while maintaining natural capital. However, it is not clear what governance is needed to achieve sustainable land use under multiple goals (as defined by the values of relevant decision-makers and land managers), particularly under climate change. Here we develop a conceptual model for examining the interactions and tradeoffs among multiple goals, as well as their spatial interactions (teleconnections), in research developed using Design Thinking principles. We have selected five metrics for provisioning (food production, and fiber production for wood and energy), regulating and maintenance (climate mitigation and biodiversity conservation), and cultural (heritage) ecosystem services. Using the case of Sweden, we estimate indicators for these metrics using a combination of existing data synthesis and process-based simulation modeling. We also develop and analyze new indicators (e.g., combining data on land use, bird conservation status, and habitat specificity to make a predictive model of bird diversity changes on agricultural or forested land). Our results highlight both expected tradeoffs (e.g., between food production and biodiversity conservation) as well as unexpected opportunities for synergies under different land management scenarios and strategies. Our model also provides a practical way to make decision-maker values explicit by comparing both quantity and preferences for bundles of ecosystem services under various scenarios. We hope our model will help in considering competing interests and shaping economic incentives and governance structures to meet national targets in support of global goals for sustainable management of land-based ecosystem services.

Retention of Afforestation Areas as Part of Flood Protection - Research Site and Methodology for Headwater Watershad in Poland / Retencja Leśna Zlewni Jako Element Ochrony Przeciwpowodziowej

NASA Astrophysics Data System (ADS)

Orczykowski, Tomasz; Tiukało, Andrzej

2016-03-01

Land use is considered as a non-structural, ecologically beneficial flood protection measure. Forest as one of the land use types has many useful applications which can be observed in detail on www.nwrm.eu website project. It is scientifically proved that afforestation influences flood events with high probability of occurrence. However, it is still to be argued how to measure land use impact on the hydrological response of watershed and how it should be measured in an efficient and quantifiable way. Having the tool for such an impact measurement, we can build efficient land management strategies. It is difficult to observe the impact of land use on flood events in the field.Therefore, one of the possible solutions is to observe this impact indirectly by means of hydrological rainfall-runoff models as a proxy for the reality. Such experiments were conducted in the past. Our study aims to work on the viability assessment, methodology and tools that allow to observe this impact with use of selected hydrological models and readily available data in Poland. Our first reaserch site is located within headwaters of the Kamienna river watershed. This watershed has been affected by ecological disaster, which resulted in loss of 65% of forest coverage. Our proposed methodology is to observe this transformation and its effect on the watershed response to heavy precipitation and therefore change in the flood risk.

On approaches to analyze the sensitivity of simulated hydrologic fluxes to model parameters in the community land model

DOE PAGES

Bao, Jie; Hou, Zhangshuan; Huang, Maoyi; ...

2015-12-04

Here, effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash-Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalizedmore » linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.« less

Quantifying ecosystem carbon losses and gains following development in New England: A combined field, modeling, and remote sensing approach

NASA Astrophysics Data System (ADS)

Raciti, S. M.; Hutyra, L.; Briber, B. M.; Dunn, A. L.; Friedl, M. A.; Woodcock, C.; Zhu, Z.; Olofsson, P.

2013-12-01

If current trends continue, the world's urban population may double and urban land area may quadruple over the next 50 years. Despite the rapid expansion of urban areas, the trajectories of carbon losses and gains following development remain poorly quantified. We are using a combination of field measurements, modeling, and remote sensing to advance our ability to measure and monitor trajectories of ecosystem carbon over space and time. To characterize how carbon stocks change across urban-to-rural gradients, we previously established field plots to survey live and dead tree biomass, tree canopy, soil and foliar carbon and nitrogen concentrations, and a range of landscape characteristics (Raciti et al. 2012). In 2013, we extended our field sampling to focus specifically on places that experienced land use and land cover change over the past 35 years. This chronosequence approach was informed by Landsat time series (1982-present) and property records (before 1982). The Landsat time series approach differs from traditional remote-sensing-based land use change detection methods because it leverages the entire Landsat archive of imagery using a Fourier fitting approach (Zhu et al. 2012). The result is a temporally and spatially continuous map of land use and land cover change across the study region. We used these field and remote sensing data to inform a carbon bookkeeping model that estimates changes in past and potential future carbon stocks over time. Here we present preliminary results of this work for eastern Massachusetts.

Impact of Soil and Water Conservation Interventions on Watershed Runoff Response in a Tropical Humid Highland of Ethiopia.

PubMed

Sultan, Dagnenet; Tsunekawa, Atsushi; Haregeweyn, Nigussie; Adgo, Enyew; Tsubo, Mitsuru; Meshesha, Derege Tsegaye; Masunaga, Tsugiyuki; Aklog, Dagnachew; Fenta, Ayele Almaw; Ebabu, Kindiye

2018-05-01

Various soil and water conservation measures (SWC) have been widely implemented to reduce surface runoff in degraded and drought-prone watersheds. But little quantitative study has been done on to what extent such measures can reduce watershed-scale runoff, particularly from typical humid tropical highlands of Ethiopia. The overall goal of this study is to analyze the impact of SWC interventions on the runoff response by integrating field measurement with a hydrological CN model which gives a quantitative analysis future thought. Firstly, a paired-watershed approach was employed to quantify the relative difference in runoff response for the Kasiry (treated) and Akusty (untreated) watersheds. Secondly, a calibrated curve number hydrological modeling was applied to investigate the effect of various SWC management scenarios for the Kasiry watershed alone. The paired-watershed approach showed a distinct runoff response between the two watersheds however the effect of SWC measures was not clearly discerned being masked by other factors. On the other hand, the model predicts that, under the current SWC coverage at Kasiry, the seasonal runoff yield is being reduced by 5.2%. However, runoff yields from Kasiry watershed could be decreased by as much as 34% if soil bunds were installed on cultivated land and trenches were installed on grazing and plantation lands. In contrast, implementation of SWC measures on bush land and natural forest would have little effect on reducing runoff. The results on the magnitude of runoff reduction under optimal combinations of SWC measures and land use will support decision-makers in selection and promotion of valid management practices that are suited to particular biophysical niches in the tropical humid highlands of Ethiopia.

The Monitoring Erosion of Agricultural Land and spatial database of erosion events

NASA Astrophysics Data System (ADS)

Kapicka, Jiri; Zizala, Daniel

2013-04-01

In 2011 originated in The Czech Republic The Monitoring Erosion of Agricultural Land as joint project of State Land Office (SLO) and Research Institute for Soil and Water Conservation (RISWC). The aim of the project is collecting and record keeping information about erosion events on agricultural land and their evaluation. The main idea is a creation of a spatial database that will be source of data and information for evaluation and modeling erosion process, for proposal of preventive measures and measures to reduce negative impacts of erosion events. A subject of monitoring is the manifestations of water erosion, wind erosion and slope deformation in which cause damaged agriculture land. A website, available on http://me.vumop.cz, is used as a tool for keeping and browsing information about monitored events. SLO employees carry out record keeping. RISWC is specialist institute in the Monitoring Erosion of Agricultural Land that performs keeping the spatial database, running the website, managing the record keeping of events, analysis the cause of origins events and statistical evaluations of keeping events and proposed measures. Records are inserted into the database using the user interface of the website which has map server as a component. Website is based on database technology PostgreSQL with superstructure PostGIS and MapServer UMN. Each record is in the database spatial localized by a drawing and it contains description information about character of event (data, situation description etc.) then there are recorded information about land cover and about grown crops. A part of database is photodocumentation which is taken in field reconnaissance which is performed within two days after notify of event. Another part of database are information about precipitations from accessible precipitation gauges. Website allows to do simple spatial analysis as are area calculation, slope calculation, percentage representation of GAEC etc.. Database structure was designed on the base of needs analysis inputs to mathematical models. Mathematical models are used for detailed analysis of chosen erosion events which include soil analysis. Till the end 2012 has had the database 135 events. The content of database still accrues and gives rise to the extensive source of data that is usable for testing mathematical models.

Acoustic test and analyses of three advanced turboprop models

NASA Technical Reports Server (NTRS)

Brooks, B. M.; Metzger, F. B.

1980-01-01

Results of acoustic tests of three 62.2 cm (24.5 inch) diameter models of the prop-fan (a small diameter, highly loaded. Multi-bladed variable pitch advanced turboprop) are presented. Results show that there is little difference in the noise produced by unswept and slightly swept designs. However, the model designed for noise reduction produces substantially less noise at test conditions simulating 0.8 Mach number cruise speed or at conditions simulating takeoff and landing. In the near field at cruise conditions the acoustically designed. In the far field at takeoff and landing conditions the acoustically designed model is 5 db quieter than unswept or slightly swept designs. Correlation between noise measurement and theoretical predictions as well as comparisons between measured and predicted acoustic pressure pulses generated by the prop-fan blades are discussed. The general characteristics of the pulses are predicted. Shadowgraph measurements were obtained which showed the location of bow and trailing waves.

Simulation of jet blast effect on landing aircraft

DOT National Transportation Integrated Search

2001-01-01

Presents a model to measure the effects of various kinds and sizes of jet blast from an airplane that is taking off on a path at right angle to and traveling away from a jet that is landing. With increasingly powerful engines and growing capacity and...

Exposure and Vulnerability Geospatial Analysis Using Earth Observation Data in the City of Liege, Belgium

NASA Astrophysics Data System (ADS)

Stephenne, N.; Beaumont, B.; Hallot, E.; Lenartz, F.; Lefebre, F.; Lauwaet, D.; Poelmans, L.; Wolff, E.

2017-05-01

Risk situation can be mitigated by prevention measures, early warning tools and adequate monitoring of past experiences where Earth Observation and geospatial analysis have an adding value. This paper discusses the potential use of Earth Observation data and especially Land Cover / Land Use map in addressing within the three aspects of the risk assessment: danger, exposure and vulnerability. Evidences of the harmful effects of air pollution or heat waves are widely admitted and should increase in the context of global warming. Moreover, urban areas are generally warmer than rural surroundings, the so-called urban heat island. Combined with in-situ measurements, this paper presents models of city or local climate (air pollution and urban heat island), with a resolution of less than one kilometer, developed by integrating several sources of information including Earth Observation data and in particular Land Cover / Land Use. This assessment of the danger is then be related to a map of exposure and vulnerable people. Using dasymetric method to disaggregate statistical information on Land Cover / Land Use data, the SmartPop project analyzes in parallel the map of danger with the maps of people exposure A special focus on some categories at risk such as the elderly has been proposed by Aubrecht and Ozceylan (2013). Perspectives of the project includes the integration of a new Land Cover / Land Use map in the danger, exposure and vulnerability models and proposition of several aspects of risk assessment with the stakeholders of Wallonia.

Methodology for finding and evaluating safe landing sites on small bodies

NASA Astrophysics Data System (ADS)

Rodgers, Douglas J.; Ernst, Carolyn M.; Barnouin, Olivier S.; Murchie, Scott L.; Chabot, Nancy L.

2016-12-01

Here we develop and demonstrate a three-step strategy for finding a safe landing ellipse for a legged spacecraft on a small body such as an asteroid or planetary satellite. The first step, acquisition of a high-resolution terrain model of a candidate landing region, is simulated using existing statistics on block abundances measured at Phobos, Eros, and Itokawa. The synthetic terrain model is generated by randomly placing hemispheric shaped blocks with the empirically determined size-frequency distribution. The resulting terrain is much rockier than typical lunar or martian landing sites. The second step, locating a landing ellipse with minimal hazards, is demonstrated for an assumed approach to landing that uses Autonomous Landing and Hazard Avoidance Technology. The final step, determination of the probability distribution for orientation of the landed spacecraft, is demonstrated for cases of differing regional slope. The strategy described here is both a prototype for finding a landing site during a flight mission and provides tools for evaluating the design of small-body landers. We show that for bodies with Eros-like block distributions, there may be >99% probability of landing stably at a low tilt without blocks impinging on spacecraft structures so as to pose a survival hazard.

Contribution towards a draft revision of recommendations 681: Propagation data required for the design of Earth-space land mobile telecommunications systems

NASA Technical Reports Server (NTRS)

Davarian, Faramaz; Bishop, Dennis

1993-01-01

Propagation models that can be used for the design of earth-space land mobile-satellite telecommunications systems are presented. These models include: empirical roadside shadowing, attenuation frequency scaling, fade and non-fade duration distribution, multipath in a mountain environment, and multipath in a roadside tree environment. Propagation data from helicopter-mobile and satellite-mobile measurements in Australia and the United States were used to develop the models.

Contribution Towards a Draft Revision of Recommendation 681 Propogation Data Required for the Design of Earth-Space Land Mobile Telecommunications Systems

NASA Technical Reports Server (NTRS)

Davarian, F.; Bishop, D.

1993-01-01

Propogation models that can be used for the design of Earth-space land mobile-satellite telecommunications systems are presented. These models include: empirical roadside shadowing, attenuation frequency scaling, fade and non-fade duration distribution, multipath in a mountain environment, and multipath in a roadside tree environment. Propogation data from helicopter-mobile and satellite-mobile measurements in Australia and the United States were used to develop the models.

A two stream radiative transfer model for scaling solar induced fluorescence from leaf to canopy

NASA Astrophysics Data System (ADS)

Quaife, T. L.

2017-12-01

Solar induced fluorescence (SIF) is becoming widely used as a proxy for gross primary productivity (GPP), in particular with the advent of its measurement by Earth Observation satellites such as OCO and GOSAT. A major attraction of SIF is that it is independent of the assumptions embedded in light use efficiency based GPP products derived from satellite missions such as MODIS. The assumptions in such products are likely not compatible with any given land surface model and hence comparing the two is problematic. On the other hand to compare land surface model predictions of GPP to satellite based SIF data requires either (a) translation of SIF into estimates of GPP, or (b) direct predictions of SIF from the land surface model itself. The former typically relies on empirical relationships, whereas the latter can make direct use of our physiological understanding of the link between photosynthesis and fluorescence at the leaf scale and is therefore preferable. Here I derive a two stream model for fluorescence that is capable of translating between leaf scale models of SIF and the canopy leaving radiance taking into account all levels of photon scattering. Other such models have been developed previously but the model described here is physically consistent with the Sellers' two stream radiative transfer scheme which is widely used in modern land surface models. Consequently any model that already employs the Sellers's scheme can use the new model without requiring modification. This includes, for example, JULES, the land surface model of the new UK Earth System Model (UKESM) and CLM, the US Community Land Model (part of the NCAR Earth System Model). The new canopy SIF model is extremely computationally efficient and can be applied to vertically inhomogeneous canopies.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Predicting Coupled Emissions of N2O, CO2 and CH4 from Arable Fields in Ireland Using the ECOSSE Model

NASA Astrophysics Data System (ADS)

Khalil, M. I.; Smith, J.; Abdalla, M.; O'Brien, P.; Smith, P.; Müller, C.

2011-12-01

Agriculture and associated land-use changes contribute a significant portion to global greenhouse gas (GHG) emissions; mainly as N2O, CO2 and CH4. Improved modelling of soil processes will greatly enhance the value of national inventories, both in terms of more accurate reporting and better mitigation policy options. In Ireland, Agriculture and Land Use, Land Use Change and Forestry, is currently a priority research focus, aimed at reducing uncertainty in estimates of GHG emissions and sinks. The ECOSSE model has several advantages, including limited meteorological and soil data requirements, compared to other models. It can simulate the impacts of land-use, management and climate change on C and N emissions and stocks for both mineral and organic soils at field and national scales. In this study, ECOSSE has been used to predict GHG emissions and SOC changes in arable lands cropped with spring barley receiving different rates of N application. The simulated outputs are evaluated against measured data available from a two-year field study. The modelled responses of N2O fluxes are found to be consistent with the measured values. The bias in the total difference between measured values and the corresponding modelled N2O fluxes was large due to the impact of a few unexpected measurements. In the fertilized fields, significant correlation between modelled and measured N2O fluxes was observed, with correlation coefficients of 0.54-0.60 and root mean square errors of 18.6-20.8 g N ha-1 d-1. The measured seasonal (crop growth period) N2O losses (integrated) were 0.41 and 0.50% of the N applied at rates of 70-79 and 140-159 kg ha-1, respectively. As a further comparison, the simulated values for the dates when measurements were taken were similarly integrated. The corresponding simulated seasonal N2O losses were 0.69 and 1.11% of the added N, suggesting an overestimation by 70-123% of the measured values. However, this could be due to missed emissions associated with the sporadic timing of measurements, from 2 to 15 day intervals. The corresponding simulated annual losses obtained by summing the modelled daily fluxes were 0.49 and 0.62% of applied N, more closely matching the measured values. The model estimated a total CO2 emission of 4.0 t C ha-1 yr-1 for plots receiving no crop residues. This is less than 58% the typical range measured (9.6 t ha-1 yr-1) in a similar Irish field receiving crop residues, 47% of the annual average (7.5±4.3 t ha-1 yr-1) for temperate regions, and 26% of the global average (5.4±0.8 t ha-1 yr-1) for croplands. The simulated CH4 emissions were found to be negligible from the arable fields. The modelled SOC content increased with increasing N application rates, but on average showed a loss of 1.06 t C ha-1 yr-1 for fields receiving no residues. Preliminary results suggest that the model can reliably be used to estimate the process-based emissions of GHGs from the arable fields. However, further analyses are needed to fully determine the uncertainty in their estimates.

Statistical modeling of urban air temperature distributions under different synoptic conditions

NASA Astrophysics Data System (ADS)

Beck, Christoph; Breitner, Susanne; Cyrys, Josef; Hald, Cornelius; Hartz, Uwe; Jacobeit, Jucundus; Richter, Katja; Schneider, Alexandra; Wolf, Kathrin

2015-04-01

Within urban areas air temperature may vary distinctly between different locations. These intra-urban air temperature variations partly reach magnitudes that are relevant with respect to human thermal comfort. Therefore and furthermore taking into account potential interrelations with other health related environmental factors (e.g. air quality) it is important to estimate spatial patterns of intra-urban air temperature distributions that may be incorporated into urban planning processes. In this contribution we present an approach to estimate spatial temperature distributions in the urban area of Augsburg (Germany) by means of statistical modeling. At 36 locations in the urban area of Augsburg air temperatures are measured with high temporal resolution (4 min.) since December 2012. These 36 locations represent different typical urban land use characteristics in terms of varying percentage coverages of different land cover categories (e.g. impervious, built-up, vegetated). Percentage coverages of these land cover categories have been extracted from different sources (Open Street Map, European Urban Atlas, Urban Morphological Zones) for regular grids of varying size (50, 100, 200 meter horizonal resolution) for the urban area of Augsburg. It is well known from numerous studies that land use characteristics have a distinct influence on air temperature and as well other climatic variables at a certain location. Therefore air temperatures at the 36 locations are modeled utilizing land use characteristics (percentage coverages of land cover categories) as predictor variables in Stepwise Multiple Regression models and in Random Forest based model approaches. After model evaluation via cross-validation appropriate statistical models are applied to gridded land use data to derive spatial urban air temperature distributions. Varying models are tested and applied for different seasons and times of the day and also for different synoptic conditions (e.g. clear and calm situations, cloudy and windy situations). Based on hourly air temperature data from our measurements in the urban area of Augsburg distinct temperature differences between locations with different urban land use characteristics are revealed. Under clear and calm weather conditions differences between mean hourly air temperatures reach values around 8°C. Whereas during cloudy and windy weather maximum differences in mean hourly air temperatures do not exceed 5°C. Differences appear usually slightly more pronounced in summer than in winter. First results from the application of statistical modeling approaches reveal promising skill of the models in terms of explained variances reaching up to 60% in leave-one-out cross-validation experiments. The contribution depicts the methodology of our approach and presents and discusses first results.

7Be solar neutrino measurement with KamLAND

NASA Astrophysics Data System (ADS)

Gando, A.; Gando, Y.; Hanakago, H.; Ikeda, H.; Inoue, K.; Ishidoshiro, K.; Ishikawa, H.; Kishimoto, Y.; Koga, M.; Matsuda, R.; Matsuda, S.; Mitsui, T.; Motoki, D.; Nakajima, K.; Nakamura, K.; Obata, A.; Oki, A.; Oki, Y.; Otani, M.; Shimizu, I.; Shirai, J.; Suzuki, A.; Tamae, K.; Ueshima, K.; Watanabe, H.; Xu, B. D.; Yamada, S.; Yamauchi, Y.; Yoshida, H.; Kozlov, A.; Takemoto, Y.; Yoshida, S.; Grant, C.; Keefer, G.; McKee, D. W.; Piepke, A.; Banks, T. I.; Bloxham, T.; Freedman, S. J.; Fujikawa, B. K.; Han, K.; Hsu, L.; Ichimura, K.; Murayama, H.; O'Donnell, T.; Steiner, H. M.; Winslow, L. A.; Dwyer, D.; Mauger, C.; McKeown, R. D.; Zhang, C.; Berger, B. E.; Lane, C. E.; Maricic, J.; Miletic, T.; Learned, J. G.; Sakai, M.; Horton-Smith, G. A.; Tang, A.; Downum, K. E.; Tolich, K.; Efremenko, Y.; Kamyshkov, Y.; Perevozchikov, O.; Karwowski, H. J.; Markoff, D. M.; Tornow, W.; Detwiler, J. A.; Enomoto, S.; Heeger, K.; Decowski, M. P.; KamLAND Collaboration

2015-11-01

We report a measurement of the neutrino-electron elastic scattering rate of 862 keV 7Be solar neutrinos based on a 165.4 kt d exposure of KamLAND. The observed rate is 582 ±94 (kt d)-1, which corresponds to an 862-keV 7Be solar neutrino flux of (3.26 ±0.52 ) ×109cm-2s-1 , assuming a pure electron-flavor flux. Comparing this flux with the standard solar model prediction and further assuming three-flavor mixing, a νe survival probability of 0.66 ±0.15 is determined from the KamLAND data. Utilizing a global three-flavor oscillation analysis, we obtain a total 7Be solar neutrino flux of (5.82 ±1.02 ) ×109cm-2s-1 , which is consistent with the standard solar model predictions.

Assessment of watershed regionalization for the land use change parameterization

NASA Astrophysics Data System (ADS)

Randusová, Beata; Kohnová, Silvia; Studvová, Zuzana; Marková, Romana; Nosko, Radovan

2016-04-01

The estimation of design discharges and water levels of extreme floods is one of the most important parts of the design process for a large number of engineering projects and studies. Floods and other natural hazards initiated by climate, soil, and land use changes are highly important in the 21st century. Flood risks and design flood estimation is particularly challenging. Methods of design flood estimation can be applied either locally or regionally. To obtain the design values in such cases where no recorded data exist, many countries have adopted procedures that fit the local conditions and requirements. One of these methods is the Soil Conservation Service - Curve number (SCS-CN) method which is often used in design flood estimation for ungauged sites. The SCS-CN method is an empirical rainfall-runoff model developed by the USDA Natural Resources Conservation Service (formerly called the Soil Conservation Service or SCS). The runoff curve number (CN) is based on the hydrological soil characteristics, land use, land management and antecedent saturation conditions of soil. This study is focused on development of the SCS-CN methodology for the changing land use conditions in Slovak basins (with the pilot site of the Myjava catchment), which regionalize actual state of land use data and actual rainfall and discharge measurements of the selected river basins. In this study the state of the water erosion and sediment transport along with a subsequent proposal of erosion control measures was analyzed as well. The regionalized SCS-CN method was subsequently used for assessing the effectiveness of this control measure to reduce runoff from the selected basin. For the determination of the sediment transport from the control measure to the Myjava basin, the SDR (Sediment Delivery Ratio) model was used.

Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Maximization-Complementary Superiority (LCMCS) Method

PubMed Central

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Xi, Xiuxiu

2015-01-01

The measurement of soil total nitrogen (TN) by hyperspectral remote sensing provides an important tool for soil restoration programs in areas with subsided land caused by the extraction of natural resources. This study used the local correlation maximization-complementary superiority method (LCMCS) to establish TN prediction models by considering the relationship between spectral reflectance (measured by an ASD FieldSpec 3 spectroradiometer) and TN based on spectral reflectance curves of soil samples collected from subsided land which is determined by synthetic aperture radar interferometry (InSAR) technology. Based on the 1655 selected effective bands of the optimal spectrum (OSP) of the first derivate differential of reciprocal logarithm ([log{1/R}]′), (correlation coefficients, p < 0.01), the optimal model of LCMCS method was obtained to determine the final model, which produced lower prediction errors (root mean square error of validation [RMSEV] = 0.89, mean relative error of validation [MREV] = 5.93%) when compared with models built by the local correlation maximization (LCM), complementary superiority (CS) and partial least squares regression (PLS) methods. The predictive effect of LCMCS model was optional in Cangzhou, Renqiu and Fengfeng District. Results indicate that the LCMCS method has great potential to monitor TN in subsided lands caused by the extraction of natural resources including groundwater, oil and coal. PMID:26213935

Mars-Moons Exploration, Reconnaissance and Landed Investigation (MERLIN)

NASA Astrophysics Data System (ADS)

Murchie, S. L.; Chabot, N. L.; Buczkowski, D.; Arvidson, R. E.; Castillo, J. C.; Peplowski, P. N.; Ernst, C. M.; Rivkin, A.; Eng, D.; Chmielewski, A. B.; Maki, J.; trebi-Ollenu, A.; Ehlmann, B. L.; Spence, H. E.; Horanyi, M.; Klingelhoefer, G.; Christian, J. A.

2015-12-01

The Mars-Moons Exploration, Reconnaissance and Landed Investigation (MERLIN) is a NASA Discovery mission proposal to explore the moons of Mars. Previous Mars-focused spacecraft have raised fundamental questions about Mars' moons: What are their origins and compositions? Why do the moons resemble primitive outer solar system D-type objects? How do geologic processes modify their surfaces? MERLIN answers these questions through a combination of orbital and landed measurements, beginning with reconnaissance of Deimos and investigation of the hypothesized Martian dust belts. Orbital reconnaissance of Phobos occurs, followed by low flyovers to characterize a landing site. MERLIN lands on Phobos, conducting a 90-day investigation. Radiation measurements are acquired throughout all mission phases. Phobos' size and mass provide a low-risk landing environment: controlled descent is so slow that the landing is rehearsed, but gravity is high enough that surface operations do not require anchoring. Existing imaging of Phobos reveals low regional slope regions suitable for landing, and provides knowledge for planning orbital and landed investigations. The payload leverages past NASA investments. Orbital imaging is accomplished by a dual multispectral/high-resolution imager rebuilt from MESSENGER/MDIS. Mars' dust environment is measured by the refurbished engineering model of LADEE/LDEX, and the radiation environment by the flight spare of LRO/CRaTER. The landed workspace is characterized by a color stereo imager updated from MER/HazCam. MERLIN's arm deploys landed instrumentation using proven designs from MER, Phoenix, and MSL. Elemental measurements are acquired by a modified version of Rosetta/APXS, and an uncooled gamma-ray spectrometer. Mineralogical measurements are acquired by a microscopic imaging spectrometer developed under MatISSE. MERLIN delivers seminal science traceable to NASA's Strategic Goals and Objectives, Science Plan, and the Decadal Survey. MERLIN's science-driven investigations also provide insight into Mars' particulate and radiation environment, Phobos' composition and regolith properties, and Phobos' inventory of in situ resources, filling strategic knowledge gaps to pioneer the way for future human exploration of the Mars system.

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

NASA Technical Reports Server (NTRS)

Gutmann, Ethan D.; Small, Eric E.

2007-01-01

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

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.

An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning.

PubMed

Wier, Megan; Weintraub, June; Humphreys, Elizabeth H; Seto, Edmund; Bhatia, Rajiv

2009-01-01

There is growing awareness among urban planning, public health, and transportation professionals that design decisions and investments that promote walking can be beneficial for human and ecological health. Planners need practical tools to consider the impact of development on pedestrian safety, a key requirement for the promotion of walking. Simple bivariate models have been used to predict changes in vehicle-pedestrian injury collisions based on changes in traffic volume. We describe the development of a multivariate, area-level regression model of vehicle-pedestrian injury collisions based on environmental and population data in 176 San Francisco, California census tracts. Predictor variables examined included street, land use, and population characteristics, including commute behaviors. The final model explained approximately 72% of the systematic variation in census-tract vehicle-pedestrian injury collisions and included measures of traffic volume, arterial streets without transit, land area, proportion of land area zoned for neighborhood commercial and residential-neighborhood commercial uses, employee and resident populations, proportion of people living in poverty and proportion aged 65 and older. We have begun to apply this model to predict area-level change in vehicle-pedestrian injury collisions associated with land use development and transportation planning decisions.

Evaluating Nitrate Contributions From Different Land Use Types Across a Regional Watershed Using Flow and Transport Models

NASA Astrophysics Data System (ADS)

Spansky, M. C.; Hyndman, D. W.; Long, D. T.; Pijanowski, B. C.

2004-05-01

Regional inputs of non-point source pollutants to groundwater, such as agriculturally-derived nitrate, have typically proven difficult to model due to sparse concentration data and complex system dynamics. We present an approach to evaluate the relative contribution of various land use types to groundwater nitrate across a regional Michigan watershed using groundwater flow and transport models. The models were parameterized based on land use data, and calibrated to a 20 year database of nitrate measured in drinking water wells. The database spans 1983-2003 and contains approximately 27,000 nitrate records for the five major counties encompassed by the watershed. The Grand Traverse Bay Watershed (GTBW), located in the northwest Lower Peninsula of Michigan, was chosen for this research. Groundwater flow and nitrate transport models were developed for the GTBW using MODFLOW2000 and RT3D, respectively. In a preliminary transport model, agricultural land uses were defined as the sole source of groundwater nitrate. Nitrate inputs were then refined to reflect variations in nitrogen loading rates for different agriculture types, including orchards, row crops, and pastureland. The calibration dataset was created by assigning spatial coordinates to each water well sample using address matching from a geographic information system (GIS). Preliminary results show that there is a significant link between agricultural sources and measured groundwater nitrate concentrations. In cases where observed concentrations remain significantly higher than simulated values, other sources of nitrate (e.g. septic tanks or abandoned agricultural fields) will be evaluated. This research will eventually incorporate temporal variations in fertilizer application rates and changing land use patterns to better represent fluid and solute fluxes at a regional scale.

Using Multitemporal Remote Sensing Imagery and Inundation Measures to Improve Land Change Estimates in Coastal Wetlands

USGS Publications Warehouse

Allen, Y.C.; Couvillion, B.R.; Barras, J.A.

2012-01-01

Remote sensing imagery can be an invaluable resource to quantify land change in coastal wetlands. Obtaining an accurate measure of land change can, however, be complicated by differences in fluvial and tidal inundation experienced when the imagery is captured. This study classified Landsat imagery from two wetland areas in coastal Louisiana from 1983 to 2010 into categories of land and water. Tide height, river level, and date were used as independent variables in a multiple regression model to predict land area in the Wax Lake Delta (WLD) and compare those estimates with an adjacent marsh area lacking direct fluvial inputs. Coefficients of determination from regressions using both measures of water level along with date as predictor variables of land extent in the WLD, were higher than those obtained using the current methodology which only uses date to predict land change. Land change trend estimates were also improved when the data were divided by time period. Water level corrected land gain in the WLD from 1983 to 2010 was 1 km 2 year -1, while rates in the adjacent marsh remained roughly constant. This approach of isolating environmental variability due to changing water levels improves estimates of actual land change in a dynamic system, so that other processes that may control delta development such as hurricanes, floods, and sediment delivery, may be further investigated. ?? 2011 Coastal and Estuarine Research Federation (outside the USA).

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

USGS Publications Warehouse

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

2012-01-01

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

Linking land-use type and stream water quality using spatial data of fecal indicator bacteria and heavy metals in the Yeongsan river basin.

PubMed

Kang, Joo-Hyon; Lee, Seung Won; Cho, Kyung Hwa; Ki, Seo Jin; Cha, Sung Min; Kim, Joon Ha

2010-07-01

This study reveals land-use factors that explain stream water quality during wet and dry weather conditions in a large river basin using two different linear models-multiple linear regression (MLR) models and constrained least squares (CLS) models. Six land-use types and three topographical parameters (size, slope, and permeability) of the watershed were incorporated into the models as explanatory variables. The suggested models were then demonstrated using a digitized elevation map in conjunction with the land-use and the measured concentration data for Escherichia coli (EC), Enterococci bacteria (ENT), and six heavy metal species collected monthly during 2007-2008 at 50 monitoring sites in the Yeongsan Watershed, Korea. The results showed that the MLR models can be a powerful tool for predicting the average concentrations of pollutants in stream water (the Nash-Sutcliffe (NS) model efficiency coefficients ranged from 0.67 to 0.95). On the other hand, the CLS models, with moderately good prediction performance (the NS coefficients ranged 0.28-0.85), were more suitable for quantifying contributions of respective land-uses to the stream water quality. The CLS models suggested that industrial and urban land-uses are major contributors to the stream concentrations of EC and ENT, whereas agricultural, industrial, and mining areas were significant sources of many heavy metal species. In addition, the slope, size, and permeability of the watershed were found to be important factors determining the extent of the contribution from each land-use type to the stream water quality. The models proposed in this paper can be considered useful tools for developing land cover guidelines and for prioritizing locations for implementing management practices to maintain stream water quality standard in a large river basin. Copyright 2010 Elsevier Ltd. All rights reserved.

Assessing land leveling needs and performance with unmanned aerial system

NASA Astrophysics Data System (ADS)

Enciso, Juan; Jung, Jinha; Chang, Anjin; Chavez, Jose Carlos; Yeom, Junho; Landivar, Juan; Cavazos, Gabriel

2018-01-01

Land leveling is the initial step for increasing irrigation efficiencies in surface irrigation systems. The objective of this paper was to evaluate potential utilization of an unmanned aerial system (UAS) equipped with a digital camera to map ground elevations of a grower's field and compare them with field measurements. A secondary objective was to use UAS data to obtain a digital terrain model before and after land leveling. UAS data were used to generate orthomosaic images and three-dimensional (3-D) point cloud data by applying the structure for motion algorithm to the images. Ground control points (GCPs) were established around the study area, and they were surveyed using a survey grade dual-frequency GPS unit for accurate georeferencing of the geospatial data products. A digital surface model (DSM) was then generated from the 3-D point cloud data before and after laser leveling to determine the topography before and after the leveling. The UAS-derived DSM was compared with terrain elevation measurements acquired from land surveying equipment for validation. Although 0.3% error or root mean square error of 0.11 m was observed between UAS derived and ground measured ground elevation data, the results indicated that UAS could be an efficient method for determining terrain elevation with an acceptable accuracy when there are no plants on the ground, and it can be used to assess the performance of a land leveling project.

Landing Characteristics of a Reentry Capsule with a Torus-Shaped Air Bag for Load Alleviation

NASA Technical Reports Server (NTRS)

McGehee, John R.; Hathaway, Melvin E.

1960-01-01

An experimental investigation has been made to determine the landing characteristics of a conical-shaped reentry capsule by using torus-shaped air bags for impact-load alleviation. An impact bag was attached below the large end of the capsule to absorb initial impact loads and a second bag was attached around the canister to absorb loads resulting from impact on the canister when the capsule overturned. A 1/6-scale dynamic model of the configuration was tested for nominal flight paths of 60 deg. and 90 deg. (vertical), a range of contact attitudes from -25 deg. to 30 deg., and a vertical contact velocity of 12.25 feet per second. Accelerations were measured along the X-axis (roll) and Z-axis (yaw) by accelerometers rigidly installed at the center of gravity of the model. Actual flight path, contact attitudes, and motions were determined from high-speed motion pictures. Landings were made on concrete and on water. The peak accelerations along the X-axis for landings on concrete were in the order of 3Og for a 0 deg. contact attitude. A horizontal velocity of 7 feet per second, corresponding to a flight path of 60 deg., had very little effect upon the peak accelerations obtained for landings on concrete. For contact attitudes of -25 deg. and 30 deg. the peak accelerations along the Z-axis were about +/- l5g, respectively. The peak accelerations measured for the water landings were about one-third lower than the peak accelerations measured for the landings on concrete. Assuming a rigid body, computations were made by using Newton's second law of motion and the force-stroke characteristics of the air bag to determine accelerations for a flight path of 90 deg. (vertical) and a contact attitude of 0 deg. The computed and experimental peak accelerations and strokes at peak acceleration were in good agreement for the model. The special scaling appears to be applicable for predicting full-scale time and stroke at peak acceleration for a landing on concrete from a 90 deg. flight path at a 0 deg. It appears that the full-scale approximately the same as those obtained from the model for the range of attitudes and flight paths investigated.

Application of Ecosystem Models to Assess Environmental Drivers of Mosquito Abundance and Virus Transmission Risk and Associated Public Health Implications of Climate and Land Use Change

NASA Astrophysics Data System (ADS)

Melton, F.; Barker, C.; Park, B.; Reisen, W.; Michaelis, A.; Wang, W.; Hashimoto, H.; Milesi, C.; Hiatt, S.; Nemani, R.

2008-12-01

The NASA Terrestrial Observation and Prediction System (TOPS) is a modeling framework that integrates satellite observations, meteorological observations, and ancillary data to support monitoring and modeling of ecosystem and land surface conditions in near real-time. TOPS provides spatially continuous gridded estimates of a suite of measurements describing environmental conditions, and these data products are currently being applied to support the development of new models capable of forecasting estimated mosquito abundance and transmission risk for mosquito-borne diseases such as West Nile virus. We present results from the modeling analyses, describe their incorporation into the California Vectorborne Disease Surveillance System, and describe possible implications of projected climate and land use change for patterns in mosquito abundance and transmission risk for West Nile virus in California.

Comparison of Land Skin Temperature from a Land Model, Remote Sensing, and In-situ Measurement

NASA Technical Reports Server (NTRS)

Wang, Aihui; Barlage, Michael; Zeng, Xubin; Draper, Clara Sophie

2014-01-01

Land skin temperature (Ts) is an important parameter in the energy exchange between the land surface and atmosphere. Here hourly Ts from the Community Land Model Version 4.0, MODIS satellite observations, and in-situ observations in 2003 were compared. Compared with the in-situ observations over four semi-arid stations, both MODIS and modeled Ts show negative biases, but MODIS shows an overall better performance. Global distribution of differences between MODIS and modeled Ts shows diurnal, seasonal, and spatial variations. Over sparsely vegetated areas, the model Ts is generally lower than the MODIS observed Ts during the daytime, while the situation is opposite at nighttime. The revision of roughness length for heat and the constraint of minimum friction velocity from Zeng et al. [2012] bring the modeled Ts closer to MODIS during the day, and have little effect on Ts at night. Five factors contributing to the Ts differences between the model and MODIS are identified, including the difficulty in properly accounting for cloud cover information at the appropriate temporal and spatial resolutions, and uncertainties in surface energy balance computation, atmospheric forcing data, surface emissivity, and MODIS Ts data. These findings have implications for the cross-evaluation of modeled and remotely sensed Ts, as well as the data assimilation of Ts observations into Earth system models.

The potential for land use change to reduce flood risk in mid-sized catchments in the Myjava region of Slovakia

NASA Astrophysics Data System (ADS)

Rončák, Peter; Lisovszki, Evelin; Szolgay, Ján; Hlavčová, Kamila; Kohnová, Silvia; Csoma, Rózsa; Poórová, Jana

2017-06-01

The effects of land use management practices on surface runoff are evident on a local scale, but evidence of their impact on the scale of a watershed is limited. This study focuses on an analysis of the impact of land use changes on the flood regime in the Myjava River basin, which is located in Western Slovakia. The Myjava River basin has an area of 641.32 km2 and is typified by the formation of fast runoff processes, intensive soil erosion, and muddy floods. The main factors responsible for these problems with flooding and soil erosion are the basin's location, geology, pedology, agricultural land use, and cropping practices. The GIS-based, spatially distributed WetSpa rainfall-runoff model was used to simulate mean daily discharges in the outlet of the basin as well as the individual components of the water balance. The model was calibrated based on the period between 1997 and 2012 with outstanding results (an NS coefficient of 0.702). Various components of runoff (e.g., surface, interflow and groundwater) and several elements of the hydrological balance (evapotranspiration and soil moisture) were simulated under various land use scenarios. Six land use scenarios (`crop', `grass', `forest', `slope', `elevation' and `optimal') were developed. The first three scenarios exhibited the ability of the WetSpa model to simulate runoff under changed land use conditions and enabled a better adjustment of the land use parameters of the model. Three other "more realistic" land use scenarios, which were based on the distribution of land use classes (arable land, grass and forest) regarding permissible slopes in the catchment, confirmed the possibility of reducing surface runoff and maximum discharges with applicable changes in land use and land management. These scenarios represent practical, realistic and realizable land use management solutions and they could be economically implemented to mitigate soil erosion processes and enhance the flood protection measures in the Myjava River basin.

Project ATLANTA (ATlanta Land-use ANalysis: Temperature and Air quality): A Study of how the Urban Landscape Affects Meteorology and Air Quality Through Time

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G.; Lo, C. P.; Kidder, Stanley Q.; Hafner, Jan; Taha, Haider; Bornstein, Robert D.; Gillies, Robert R.; Gallo, Kevin P.

1998-01-01

It is our intent through this investigation to help facilitate measures that can be Project ATLANTA (ATlanta Land-use ANalysis: applied to mitigate climatological or air quality Temperature and Air-quality) is a NASA Earth degradation, or to design alternate measures to sustain Observing System (EOS) Interdisciplinary Science or improve the overall urban environment in the future. investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta. The primary objectives for this research effort are: 1) To In the last half of the 20th century, Atlanta, investigate and model the relationship between Atlanta Georgia has risen as the premier commercial, urban growth, land cover change, and the development industrial, and transportation urban area of the of the urban heat island phenomenon through time at southeastern United States. The rapid growth of the nested spatial scales from local to regional; 2) To Atlanta area, particularly within the last 25 years, has investigate and model the relationship between Atlanta made Atlanta one of the fastest growing metropolitan urban growth and land cover change on air quality areas in the United States. The population of the through time at nested spatial scales from local to Atlanta metropolitan area increased 27% between 1970 regional; and 3) To model the overall effects of urban and 1980, and 33% between 1980-1990 (Research development on surface energy budget characteristics Atlanta, Inc., 1993). Concomitant with this high rate of across the Atlanta urban landscape through time at population growth, has been an explosive growth in nested spatial scales from local to regional. Our key retail, industrial, commercial, and transportation goal is to derive a better scientific understanding of how services within the Atlanta region. This has resulted in land cover changes associated with urbanization in the tremendous land cover change dynamics within the Atlanta area, principally in transforming forest lands to metropolitan region, wherein urbanization has urban land covers through time, has, and will, effect consumed vast acreas of land adjacent to the city local and regional climate, surface energy flux, and air proper and has pushed the rural/urban fringe farther quality characteristics. Allied with this goal is the and farther away from the original Atlanta urban core. prospect that the results from this research can be An enormous transition of land from forest and applied by urban planners, environmental managers agriculture to urban land uses has occurred in the and other decision-makers, for determining how Atlanta area in the last 25 years, along with subsequent urbanization has impacted the climate and overall

Soil Moisture Controls on Rainfall and Temperature Variability: A Modeler Searches Through Observational Data

NASA Technical Reports Server (NTRS)

Koster, Randal

2010-01-01

The degree to which atmospheric processes respond to variations in soil moisture - a potentially important but largely untapped element of subseasonal to seasonal prediction - can be determined easily and directly for an atmospheric model but cannot be determined directly for nature through an analysis of observations. In atmospheric models) directions of causality can be artificially manipulated; we can avoid difficulties associated with the fact that atmospheric variations have a much larger impact on land state variations than vice-versa. In nature) on the other hand) the dominant direction of causality (the atmosphere forcing the ground) cannot be artificially "turned off") and the statistics associated with this dominant direction overwhelm those of the feedback signal. Observational data) however) do allow a number of indirect measures of landatmosphere feedback. This seminar reports on a series of joint analyses of observational and model data designed to illuminate the degree of land-atmosphere feedback present in the real world. The indirect measures do in fact suggest that feedback in nature, though small) is significant - enough to warrant the development of realistic land initialization strategies for subseasonal and seasonal forecasts.

Climate and the equilibrium state of land surface hydrology parameterizations

NASA Technical Reports Server (NTRS)

Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

For given climatic rates of precipitation and potential evaporation, the land surface hydrology parameterizations of atmospheric general circulation models will maintain soil-water storage conditions that balance the moisture input and output. The surface relative soil saturation for such climatic conditions serves as a measure of the land surface parameterization state under a given forcing. The equilibrium value of this variable for alternate parameterizations of land surface hydrology are determined as a function of climate and the sensitivity of the surface to shifts and changes in climatic forcing are estimated.

Using the FORE-SCE model to project land-cover change in the southeastern United States

USGS Publications Warehouse

Sohl, Terry; Sayler, Kristi L.

2008-01-01

A wide variety of ecological applications require spatially explicit current and projected land-use and land-cover data. The southeastern United States has experienced massive land-use change since European settlement and continues to experience extremely high rates of forest cutting, significant urban development, and changes in agricultural land use. Forest-cover patterns and structure are projected to change dramatically in the southeastern United States in the next 50 years due to population growth and demand for wood products [Wear, D.N., Greis, J.G. (Eds.), 2002. Southern Forest Resource Assessment. General Technical Report SRS-53. U.S. Department of Agriculture, Forest Service, Southern Research Station, Asheville, NC, 635 pp]. Along with our climate partners, we are examining the potential effects of southeastern U.S. land-cover change on regional climate. The U.S. Geological Survey (USGS) Land Cover Trends project is analyzing contemporary (1973-2000) land-cover change in the conterminous United States, providing ecoregion-by-ecoregion estimates of the rates of change, descriptive transition matrices, and changes in landscape metrics. The FORecasting SCEnarios of future land-cover (FORE-SCE) model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land-cover change through 2050 for the southeastern United States. Prescriptions for future proportions of land cover for this application were provided by ecoregion-based extrapolations of historical change. Logistic regression was used to develop relationships between suspected drivers of land-cover change and land cover, resulting in the development of probability-of-occurrence surfaces for each unique land-cover type. Forest stand age was initially established with Forest Inventory and Analysis (FIA) data and tracked through model iterations. The spatial allocation procedure placed patches of new land cover on the landscape until the scenario prescriptions were met, using measured Land Cover Trends data to guide patch characteristics and the probability surfaces to guide placement. The approach provides an efficient method for extrapolating historical land-cover trends and is amenable to the incorporation of more detailed and focused studies for the establishment of scenario prescriptions.

Project ATLANTA (Atlanta Land use Analysis: Temperature and Air Quality): Use of Remote Sensing and Modeling to Analyze How Urban Land Use Change Affects Meteorology and Air Quality Through Time

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G., Jr.

1999-01-01

This paper presents an overview of Project ATLANTA (ATlanta Land use ANalysis: Temperature and Air-quality) which is an investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta, Georgia metropolitan area since the early 1970's has impacted the region's climate and air quality. The primary objectives for this research effort are: (1) To investigate and model the relationships between land cover change in the Atlanta metropolitan, and the development of the urban heat island phenomenon through time; (2) To investigate and model the temporal relationships between Atlanta urban growth and land cover change on air quality; and (3) To model the overall effects of urban development on surface energy budget characteristics across the Atlanta urban landscape through time. Our key goal is to derive a better scientific understanding of how land cover changes associated with urbanization in the Atlanta area, principally in transforming forest lands to urban land covers through time, has, and will, effect local and regional climate, surface energy flux, and air quality characteristics. Allied with this goal is the prospect that the results from this research can be applied by urban planners, environmental managers and other decision-makers, for determining how urbanization has impacted the climate and overall environment of the Atlanta area. Multiscaled remote sensing data, particularly high resolution thermal infrared data, are integral to this study for the analysis of thermal energy fluxes across the Atlanta urban landscape.

Disentangling Climate and Land-use Impacts on Grassland Carbon and Water Fluxes

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Nippert, J. B.

2014-12-01

Regional climate and land cover interact in a complex, non-linear manner to alter the local cycling of mass and energy. It is often difficult to isolate the role of either mechanism on the resultant fluxes. Here, we attempt to isolate these mechanisms through the use of network of 4 Ameriflux eddy covariance towers installed over different land cover and land use classes along a pronounced rainfall gradient. The land cover types include: annually burned C4 grassland, a 4 year burn site experiencing woody encroachment, an abandoned agricultural field and a new perennial agricultural site. We investigated the impact of rainfall variability, drought, and heat waves on the water and carbon budgets using data analysis, remote sensing, and modeling approaches. In addition, we have established a network of mini-meteorological stations at the annually and 4-year burn sites to assess micro-scale variability within the footprints of the towers as a function of topographic position, soil depth and soil water availability. Through the use of a wavelet multiscale decomposition and information theory metrics, we have isolated the role of environmental factors (temperature, humidity, soil moisture, etc.) on the fluxes across the different sites. By applying a similar analysis to model output, we can assess the ability of land-surface models to recreate the observed sensitity. Results indicate the utility of a network of measurement systems used in conjunction with land surface modeling and time series analysis to assess differential impacts to similar regional scale climate forcings. Implications for the role of land cover class in regional and global scale modeling systems will also be discussed.

A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

USGS Publications Warehouse

Thomas, D.L.; Johnson, D.; Griffith, B.

2006-01-01

Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a Bayesian hierarchical discrete-choice model for resource selection can provide managers with 2 components of population-level inference: average population selection and variability of selection. Both components are necessary to make sound management decisions based on animal selection.

Sensitivity of biogenic volatile organic compounds to land surface parameterizations and vegetation distributions in California

NASA Astrophysics Data System (ADS)

Zhao, Chun; Huang, Maoyi; Fast, Jerome D.; Berg, Larry K.; Qian, Yun; Guenther, Alex; Gu, Dasa; Shrivastava, Manish; Liu, Ying; Walters, Stacy; Pfister, Gabriele; Jin, Jiming; Shilling, John E.; Warneke, Carsten

2016-05-01

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model with chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Wang, Yansen; Tao, W.-K.; Lau, K.-M.; Wetzel, Peter J.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated by coupling a mesoscale atmospheric model (MM5) and a detailed, land surface model, PLACE (the Parameterization for Land-Atmosphere-Cloud Exchange). The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The control simulation with the PLACE land surface model and variable sea surface temperature captured the basic signatures of the monsoon onset processes and associated rainfall statistics. Sensitivity tests indicated that simulations were sigmficantly improved by including the PLACE land surface model. The mechanism by which the land surface processes affect the moisture transport and the convection during the onset of the southeast Asian monsoon were analyzed. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation: the southwest low-level flow over the Indo-china peninsula and the northern, cold frontal intrusion from southern China. The surface sensible and latent heat fluxes modified the low-level temperature distribution and gradient, and therefore the low-level wind due to the thermal wind effect. The more realistic forcing of the sensible and latent heat fluxes from the detailed, land surface model improved the low-level wind simulation apd associated moisture transport and convection.

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Wang, Yansen; Tao, W.-K.; Lau, K.-M.; Wetzel, Peter J.

2004-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated by coupling a mesoscale atmospheric model (MM5) and a detailed, land surface model, PLACE (the Parameterization for Land-Atmosphere-Cloud Exchange). The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The control simulation with the PLACE land surface model and variable sea surface temperature captured the basic signatures of the monsoon onset processes and associated rainfall statistics. Sensitivity tests indicated that simulations were significantly improved by including the PLACE land surface model. The mechanism by which the land surface processes affect the moisture transport and the convection during the onset of the southeast Asian monsoon were analyzed. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation: the southwest low-level flow over the Indo-China peninsula and the northern, cold frontal intrusion from southern China. The surface sensible and latent heat fluxes modified the low-level temperature distribution and merit, and therefore the low-level wind due to the thermal wind effect. The more realistic forcing of the sensible and latent heat fluxes from the detailed, land surface model improved the low-level wind simulation and associated moisture transport and convection.

Assessing temporally and spatially resolved PM 2.5 exposures for epidemiological studies using satellite aerosol optical depth measurements

NASA Astrophysics Data System (ADS)

Kloog, Itai; Koutrakis, Petros; Coull, Brent A.; Lee, Hyung Joo; Schwartz, Joel

2011-11-01

Land use regression (LUR) models provide good estimates of spatially resolved long-term exposures, but are poor at capturing short term exposures. Satellite-derived Aerosol Optical Depth (AOD) measurements have the potential to provide spatio-temporally resolved predictions of both long and short term exposures, but previous studies have generally showed relatively low predictive power. Our objective was to extend our previous work on day-specific calibrations of AOD data using ground PM 2.5 measurements by incorporating commonly used LUR variables and meteorological variables, thus benefiting from both the spatial resolution from the LUR models and the spatio-temporal resolution from the satellite models. Later we use spatial smoothing to predict PM 2.5 concentrations for day/locations with missing AOD measures. We used mixed models with random slopes for day to calibrate AOD data for 2000-2008 across New-England with monitored PM 2.5 measurements. We then used a generalized additive mixed model with spatial smoothing to estimate PM 2.5 in location-day pairs with missing AOD, using regional measured PM 2.5, AOD values in neighboring cells, and land use. Finally, local (100 m) land use terms were used to model the difference between grid cell prediction and monitored value to capture very local traffic particles. Out-of-sample ten-fold cross-validation was used to quantify the accuracy of our predictions. For days with available AOD data we found high out-of-sample R2 (mean out-of-sample R2 = 0.830, year to year variation 0.725-0.904). For days without AOD values, our model performance was also excellent (mean out-of-sample R2 = 0.810, year to year variation 0.692-0.887). Importantly, these R2 are for daily, rather than monthly or yearly, values. Our model allows one to assess short term and long-term human exposures in order to investigate both the acute and chronic effects of ambient particles, respectively.

Observational Evaluation of Simulated Land-Atmosphere Coupling on the U.S. Southern Great Plains

NASA Astrophysics Data System (ADS)

Phillips, T. J.; Klein, S. A.

2014-12-01

In a recent study of observed features of land-atmosphere coupling (LAC) at the ARM Southern Great Plains (ARM SGP) site in northern Oklahoma (Phillips and Klein, 2014 Journal of Geophysical Research), we identified statistically significant interactions between 1997-2008 summertime daily averages of soil moisture (at 10 cm depth) and a number of surface atmospheric variables, such as surface evaporation, relative humidity, and temperature. Here we will report on an evaluation of similar features of LAC simulated by version 5 of the global Community Atmosphere Model (CAM5), coupled to its native CLM4 land model, and downscaled to the vicinity of the ARM SGP site. In these case studies, the CAM5 was initialized from a 6-hourly atmospheric reanalysis for each day of the years 2008 and 2009 (where the CLM4 land state was equilibrated to the atmospheric model state), thus permitting a close comparison of the modeled and observed summer daily average features of the LAC in these years. Correlation coefficients R and "sensitivity indices" I (a measure of the comparative change of an atmospheric variable for a one-standard-deviation change in soil moisture) provided quantitative measures of the respective coupling strengths. Such a comparison of observed versus modeled LAC is complicated by differences in atmospheric forcings of the land; for example, the CAM5's summertime precipitation is too scant, and thus the model's upper soil layer often is drier than observed. The modeled daily average covariations of soil moisture with lower atmospheric variables also display less coherence (lower R values), but sometimes greater "sensitivity" (higher I values) than are observed at the ARM SGP site. Since the observational estimate of LAC may itself be sensitive to soil moisture measurement biases, we also will report on a planned investigation of the dependence of LAC on several alternative choices of soil moisture data sets local to the ARM SGP site. AcknowledgmentsThis work was funded by the U.S. Department of Energy Office of Science and was performed at the Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Validation of the North American Land Data Assimilation System (NLDAS) retrospective forcing over the southern Great Plains

NASA Astrophysics Data System (ADS)

Luo, Lifeng; Robock, Alan; Mitchell, Kenneth E.; Houser, Paul R.; Wood, Eric F.; Schaake, John C.; Lohmann, Dag; Cosgrove, Brian; Wen, Fenghua; Sheffield, Justin; Duan, Qingyun; Higgins, R. Wayne; Pinker, Rachel T.; Tarpley, J. Dan

2003-11-01

Atmospheric forcing used by land surface models is a critical component of the North American Land Data Assimilation System (NLDAS) and its quality crucially affects the final product of NLDAS and our work on model improvement. A three-year (September 1996-September 1999) retrospective forcing data set was created from the Eta Data Assimilation System and observations and used to run the NLDAS land surface models for this period. We compared gridded NLDAS forcing with station observations obtained from networks including the Oklahoma Mesonet and Atmospheric Radiation Measurement/Cloud and Radiation Testbed at the southern Great Plains. Differences in all forcing variables except precipitation between the NLDAS forcing data set and station observations are small at all timescales. While precipitation data do not agree very well at an hourly timescale, they do agree better at longer timescales because of the way NLDAS precipitation forcing is generated. A small high bias in downward solar radiation and a low bias in downward longwave radiation exist in the retrospective forcing. To investigate the impact of these differences on land surface modeling we compared two sets of model simulations, one forced by the standard NLDAS product and one with station-observed meteorology. The differences in the resulting simulations of soil moisture and soil temperature for each model were small, much smaller than the differences between the models and between the models and observations. This indicates that NLDAS retrospective forcing provides an excellent state-of-the-art data set for land surface modeling, at least over the southern Great Plains region.

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

Modeling spatially-varying landscape change points in species occurrence thresholds

USGS Publications Warehouse

Wagner, Tyler; Midway, Stephen R.

2014-01-01

Predicting species distributions at scales of regions to continents is often necessary, as large-scale phenomena influence the distributions of spatially structured populations. Land use and land cover are important large-scale drivers of species distributions, and landscapes are known to create species occurrence thresholds, where small changes in a landscape characteristic results in abrupt changes in occurrence. The value of the landscape characteristic at which this change occurs is referred to as a change point. We present a hierarchical Bayesian threshold model (HBTM) that allows for estimating spatially varying parameters, including change points. Our model also allows for modeling estimated parameters in an effort to understand large-scale drivers of variability in land use and land cover on species occurrence thresholds. We use range-wide detection/nondetection data for the eastern brook trout (Salvelinus fontinalis), a stream-dwelling salmonid, to illustrate our HBTM for estimating and modeling spatially varying threshold parameters in species occurrence. We parameterized the model for investigating thresholds in landscape predictor variables that are measured as proportions, and which are therefore restricted to values between 0 and 1. Our HBTM estimated spatially varying thresholds in brook trout occurrence for both the proportion agricultural and urban land uses. There was relatively little spatial variation in change point estimates, although there was spatial variability in the overall shape of the threshold response and associated uncertainty. In addition, regional mean stream water temperature was correlated to the change point parameters for the proportion of urban land use, with the change point value increasing with increasing mean stream water temperature. We present a framework for quantify macrosystem variability in spatially varying threshold model parameters in relation to important large-scale drivers such as land use and land cover. Although the model presented is a logistic HBTM, it can easily be extended to accommodate other statistical distributions for modeling species richness or abundance.

Simulating Soil Organic Carbon Stock Changes in Agro-ecosystems using CQESTR, DayCent, and IPCC Tier 1 Methods

USDA-ARS?s Scientific Manuscript database

Models are often used to quantify how land use change and management impact soil organic carbon (SOC) stocks because it is often not feasible to use direct measuring methods. Because models are simplifications of reality, it is essential to compare model outputs with measured values to evaluate mode...

Simulation of the Onset of the Southeast Asian Monsoon During 1997 and 1998: The Impact of Surface Processes

NASA Technical Reports Server (NTRS)

Wang, Yansen; Tao, W.-K.; Lau, K.-M.; Wetzel, Peter J.

2003-01-01

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated with a coupled mesoscale atmospheric model (MM5) and a detailed land surface model. The rainfall results from the simulations were compared with observed satellite data fiom the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The simulation with the land surface model captured basic signatures of the monsoon onset processes and associated rainfall statistics. The sensitivity tests indicated that land surface processes had a greater impact on the simulated rainfall results than that of a small sea surface temperature change during the onset period. In both the 1997 and 1998 cases, the simulations were significantly improved by including the land surface processes. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation; the southwest low-level flow over the Indo- China peninsula and the northern cold front intrusion from southern China. The surface sensible and latent heat exchange between the land and atmosphere modified the lowlevel temperature distribution and gradient, and therefore the low-level. The more realistic forcing of the sensible and latent heat from the detailed land surface model improved the monsoon rainfall and associated wind simulation.

Landsat - What is operational in water resources

NASA Technical Reports Server (NTRS)

Middleton, E. M.; Munday, J. C., Jr.

1981-01-01

Applications of Landsat data in hydrology and water quality measurement were examined to determine which applications are operational. In hydrology, the principal applications have been surface water inventory, and land cover analysis for (1) runoff modeling and (2) abatement planning for non-point pollution and erosion. In water quality measurement, the principal applications have been: (1) trophic state assessment, and (2) measurement of turbidity and suspended sediment. The following applications were found to be operational: mapping of surface water, snow cover, and land cover (USGS Level 1) for watershed applications; measurement of turbidity, Secchi disk depth, suspended sediment concentration, and water depth.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Aerodynamic Measurements of a Gulfstream Aircraft Model With and Without Noise Reduction Concepts

NASA Technical Reports Server (NTRS)

Neuhart, Dan H.; Hannon, Judith A.; Khorrami, Mehdi R.

2014-01-01

Steady and unsteady aerodynamic measurements of a high-fidelity, semi-span 18% scale Gulfstream aircraft model are presented. The aerodynamic data were collected concurrently with acoustic measurements as part of a larger aeroacoustic study targeting airframe noise associated with main landing gear/flap components, gear-flap interaction noise, and the viability of related noise mitigation technologies. The aeroacoustic tests were conducted in the NASA Langley Research Center 14- by 22-Foot Subsonic Wind Tunnel with the facility in the acoustically treated open-wall (jet) mode. Most of the measurements were obtained with the model in landing configuration with the flap deflected at 39º and the main landing gear on and off. Data were acquired at Mach numbers of 0.16, 0.20, and 0.24. Global forces (lift and drag) and extensive steady and unsteady surface pressure measurements were obtained. Comparison of the present results with those acquired during a previous test shows a significant reduction in the lift experienced by the model. The underlying cause was traced to the likely presence of a much thicker boundary layer on the tunnel floor, which was acoustically treated for the present test. The steady and unsteady pressure fields on the flap, particularly in the regions of predominant noise sources such as the inboard and outboard tips, remained unaffected. It is shown that the changes in lift and drag coefficients for model configurations fitted with gear/flap noise abatement technologies fall within the repeatability of the baseline configuration. Therefore, the noise abatement technologies evaluated in this experiment have no detrimental impact on the aerodynamic performance of the aircraft model.

Mars Science Laboratory Entry, Descent, and Landing Trajectory and Atmosphere Reconstruction

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.; Kutty, Prasad; Schoenenberer, Mark; Shidner, Jeremy D.

2013-01-01

On August 5th 2012, The Mars Science Laboratory entry vehicle successfully entered Mars atmosphere and landed the Curiosity rover on its surface. A Kalman filter approach has been implemented to reconstruct the entry, descent, and landing trajectory based on all available data. The data sources considered in the Kalman filtering approach include the inertial measurement unit accelerations and angular rates, the terrain descent sensor, the measured landing site, orbit determination solutions for the initial conditions, and a new set of instrumentation for planetary entry reconstruction consisting of forebody pressure sensors, known as the Mars Entry Atmospheric Data System. These pressure measurements are unique for planetary entry, descent, and landing reconstruction as they enable a reconstruction of the freestream atmospheric conditions without any prior assumptions being made on the vehicle aerodynamics. Moreover, the processing of these pressure measurements in the Kalman filter approach enables the identification of atmospheric winds, which has not been accomplished in past planetary entry reconstructions. This separation of atmosphere and aerodynamics allows for aerodynamic model reconciliation and uncertainty quantification, which directly impacts future missions. This paper describes the mathematical formulation of the Kalman filtering approach, a summary of data sources and preprocessing activities, and results of the reconstruction.

A measurement model for real estate bubble size based on the panel data analysis: An empirical case study

PubMed Central

Liu, Fengyun; Liu, Deqiang; Malekian, Reza; Li, Zhixiong; Wang, Deqing

2017-01-01

Employing the fundamental value of real estate determined by the economic fundamentals, a measurement model for real estate bubble size is established based on the panel data analysis. Using this model, real estate bubble sizes in various regions in Japan in the late 1980s and in recent China are examined. Two panel models for Japan provide results, which are consistent with the reality in the 1980s where a commercial land price bubble appeared in most area and was much larger than that of residential land. This provides evidence of the reliability of our model, overcoming the limit of existing literature with this method. The same models for housing prices in China at both the provincial and city levels show that contrary to the concern of serious housing price bubble in China, over-valuing in recent China is much smaller than that in 1980s Japan. PMID:28273141

A measurement model for real estate bubble size based on the panel data analysis: An empirical case study.

PubMed

Liu, Fengyun; Liu, Deqiang; Malekian, Reza; Li, Zhixiong; Wang, Deqing

2017-01-01

Employing the fundamental value of real estate determined by the economic fundamentals, a measurement model for real estate bubble size is established based on the panel data analysis. Using this model, real estate bubble sizes in various regions in Japan in the late 1980s and in recent China are examined. Two panel models for Japan provide results, which are consistent with the reality in the 1980s where a commercial land price bubble appeared in most area and was much larger than that of residential land. This provides evidence of the reliability of our model, overcoming the limit of existing literature with this method. The same models for housing prices in China at both the provincial and city levels show that contrary to the concern of serious housing price bubble in China, over-valuing in recent China is much smaller than that in 1980s Japan.

Improving the Understanding and Model Representation of Processes that Couple Shallow Clouds, Aerosols, and Land-Ecosystems

NASA Astrophysics Data System (ADS)

Fast, J. D.; Berg, L. K.; Schmid, B.; Alexander, M. L. L.; Bell, D.; D'Ambro, E.; Hubbe, J. M.; Liu, J.; Mei, F.; Pekour, M. S.; Pinterich, T.; Schobesberger, S.; Shilling, J.; Springston, S. R.; Thornton, J. A.; Tomlinson, J. M.; Wang, J.; Zelenyuk, A.

2016-12-01

Cumulus convection is an important component in the atmospheric radiation budget and hydrologic cycle over the southern Great Plains and over many regions of the world, particularly during the summertime growing season when intense turbulence induced by surface radiation couples the land surface to clouds. Current convective cloud parameterizations, however, contain uncertainties resulting from insufficient coincident data that couples cloud macrophysical and microphysical properties to inhomogeneity in surface layer, boundary layer, and aerosol properties. We describe the measurement strategy and preliminary findings from the recent Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign conducted in May and September of 2016 in the vicinity of the DOE's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site located in Oklahoma. The goal of the HI-SCALE campaign is to provide a detailed set of aircraft and surface measurements needed to obtain a more complete understanding and improved parameterizations of the lifecycle of shallow clouds. The sampling is done in two periods, one in the spring and the other in the late summer to take advantage of variations in the "greenness" for various types of vegetation, new particle formation, anthropogenic enhancement of biogenic secondary organic aerosol (SOA), and other aerosol properties. The aircraft measurements will be coupled with extensive routine ARM SGP measurements as well as Large Eddy Simulation (LES), cloud resolving, and cloud-system resolving models. Through these integrated analyses and modeling studies, the affects of inhomogeneity in land use, vegetation, soil moisture, convective eddies, and aerosol properties on the evolution of shallow clouds will be determined, including the feedbacks of cloud radiative effects.

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

A Comparative Study of Simulated and Measured Main Landing Gear Noise for Large Civil Transports

NASA Technical Reports Server (NTRS)

Konig, Benedikt; Fares, Ehab; Ravetta, Patricio; Khorrami, Mehdi R.

2017-01-01

Computational results for the NASA 26%-scale model of a six-wheel main landing gear with and without a toboggan-shaped noise reduction fairing are presented. The model is a high-fidelity representation of a Boeing 777-200 aircraft main landing gear. A lattice Boltzmann method was used to simulate the unsteady flow around the model in isolation. The computations were conducted in free-air at a Mach number of 0.17, matching a recent acoustic test of the same gear model in the Virginia Tech Stability Wind Tunnel in its anechoic configuration. Results obtained on a set of grids with successively finer spatial resolution demonstrate the challenge in resolving/capturing the flow field for the smaller components of the gear and their associated interactions, and the resulting effects on the high-frequency segment of the farfield noise spectrum. Farfield noise spectra were computed based on an FWH integral approach, with simulated pressures on the model solid surfaces or flow-field data extracted on a set of permeable surfaces enclosing the model as input. Comparison of these spectra with microphone array measurements obtained in the tunnel indicated that, for the present complex gear model, the permeable surfaces provide a more accurate representation of farfield noise, suggesting that volumetric effects are not negligible. The present study also demonstrates that good agreement between simulated and measured farfield noise can be achieved if consistent post-processing is applied to both physical and synthetic pressure records at array microphone locations.

The loss of ecosystem services due to land degradation. Integration of mechanistic and probabilistic models in an Ethiopian case study

NASA Astrophysics Data System (ADS)

Cerretelli, Stefania; Poggio, Laura; Gimona, Alessandro; Peressotti, Alessandro; Black, Helaina

2017-04-01

Land and soil degradation are widespread especially in dry and developing countries such as Ethiopia. Land degradation leads to ecosystems services (ESS) degradation, because it causes the depletion and loss of several soil functions. Ethiopia's farmland faces intense degradation due to deforestation, agricultural land expansion, land overexploitation and overgrazing. In this study we modelled the impact of physical factors on ESS degradation, in particular soil erodibility, carbon storage and nutrient retention, in the Ethiopian Great Rift Valley, northwestern of Hawassa. We used models of the Sediment retention/loss, the Nutrient Retention/loss (from the software suite InVEST) and Carbon Storage. To run the models we coupled soil local data (such as soil organic carbon, soil texture) with remote sensing data as input in the parametrization phase, e.g. to derive a land use map, to calculate the aboveground and belowground carbon, the evapotraspiration coefficient and the capacity of vegetation to retain nutrient. We then used spatialised Bayesian Belief Networks (sBBNs) predicting ecosystem services degradation on the basis of the results of the three mechanistic models. The results show i) the importance of mapping of ESS degradation taking into consideration the spatial heterogeneity and the cross-correlations between impacts ii) the fundamental role of remote sensing data in monitoring and modelling in remote, data-poor areas and iii) the important role of spatial BBNs in providing spatially explicit measures of risk and uncertainty. This approach could help decision makers to identify priority areas for intervention in order to reduce land and ecosystem services degradation.

Comprehensive evaluation of land quality basing on 3S technology and farmers' survey: A case study in Crisscross Region of Wind-drift Sand Regions along the Great Wall and Loess Plateau

NASA Astrophysics Data System (ADS)

Zhang, Yan-yu; Wang, Jing; Shi, Yan-xi; Li, Yu-huan; Lv, Chun-yan

2005-10-01

The Crisscross Region of Wind-drift Sand Regions along the Great Wall and Loess Plateau locates in southern Ordos Plateau and northern Chinese Loess Plateau, where wind erosion and water erosion coexist and specified environmental and socio-economic factors, especially human activities induce serious land degradation. However, there are only a few studies provide an overall assessment consequences. Integrated land quality assessment considering impacts of soil, topography, vegetation, environmental hazards, social-economic factors and land managements are imperative to the regional sustainable land managements. A pilot study was made in Hengshan County (Shanxi Province) with the objective of developing comprehensive land quality evaluation model integrating data from farmers' survey and Remote Sensing. Surveys were carried out in 107 households of study area in 2003 and 2004 to get farmers' perceptions of land quality and to collect correlative information. It was found out that farmers evaluated land quality by slope, water availability, soil texture, yields, amount of fertilizer, crop performance, sandy erosion degree and water erosion degree. Scientists' indicators which emphasize on getting information by RS technology were introduced to reflecting above indicators information for the sake of developing a rapid, efficient and local-fitted land quality assessment model including social-economic, environmental and anthropogenic factors. Data from satellite and surveys were integrated with socio-economic statistic data using geographical information system (GIS) and three indexes, namely Production Press Index (PPI), Land State Index (LSI) and Farmer Behavior Index (FBI) were proposed to measure different aspects of land quality. A model was further derived from the three indexes to explore the overall land quality of the study area. Results suggest that local land prevalently had a poor quality. This paper shows that whilst the model was competent for its work in the study area and evaluation results would supply beneficial information for management decisions.

Soil erosion by snow gliding - a first quantification attempt in a sub-alpine area, Switzerland

NASA Astrophysics Data System (ADS)

Meusburger, K.; Leitinger, G.; Mabit, L.; Mueller, M. H.; Walter, A.; Alewell, C.

2014-03-01

Snow processes might be one important driver of soil erosion in Alpine grasslands and thus the unknown variable when erosion modelling is attempted. The aim of this study is to assess the importance of snow gliding as soil erosion agent for four different land use/land cover types in a sub-alpine area in Switzerland. We used three different approaches to estimate soil erosion rates: sediment yield measurements in snow glide deposits, the fallout radionuclide 137Cs, and modelling with the Revised Universal Soil Loss Equation (RUSLE). The RUSLE model is suitable to estimate soil loss by water erosion, while the 137Cs method integrates soil loss due to all erosion agents involved. Thus, we hypothesise that the soil erosion rates determined with the 137Cs method are higher and that the observed discrepancy between the soil erosion rate of RUSLE and the 137Cs method is related to snow gliding and sediment concentrations in the snow glide deposits. Cumulative snow glide distance was measured for the sites in the winter 2009/10 and modelled for the surrounding area with the Spatial Snow Glide Model (SSGM). Measured snow glide distance ranged from 2 to 189 cm, with lower values at the north facing slopes. We observed a reduction of snow glide distance with increasing surface roughness of the vegetation, which is important information with respect to conservation planning and expected land use changes in the Alps. Our hypothesis was confirmed: the difference of RUSLE and 137Cs erosion rates was related to the measured snow glide distance (R2= 0.64; p < 0.005) and snow sediment yields (R2 = 0.39; p = 0.13). A high difference (lower proportion of water erosion compared to total net erosion) was observed for high snow glide rates and vice versa. The SSGM reproduced the relative difference of the measured snow glide values under different land uses and land cover types. The resulting map highlighted the relevance of snow gliding for large parts of the investigated area. Based on these results, we conclude that snow gliding is a key process impacting soil erosion pattern and magnitude in sub-alpine areas with similar topographic and climatic conditions.

State Estimation for Landing Maneuver on High Performance Aircraft

NASA Astrophysics Data System (ADS)

Suresh, P. S.; Sura, Niranjan K.; Shankar, K.

2018-01-01

State estimation methods are popular means for validating aerodynamic database on aircraft flight maneuver performance characteristics. In this work, the state estimation method during landing maneuver is explored for the first of its kind, using upper diagonal adaptive extended Kalman filter (UD-AEKF) with fuzzy based adaptive tunning of process noise matrix. The mathematical model for symmetrical landing maneuver consists of non-linear flight mechanics equation representing Aircraft longitudinal dynamics. The UD-AEKF algorithm is implemented in MATLAB environment and the states with bias is considered to be the initial conditions just prior to the flare. The measurement data is obtained from a non-linear 6 DOF pilot in loop simulation using FORTRAN. These simulated measurement data is additively mixed with process and measurement noises, which are used as an input for UD-AEKF. Then, the governing states that dictate the landing loads at the instant of touch down are compared. The method is verified using flight data wherein, the vertical acceleration at the aircraft center of gravity (CG) is compared. Two possible outcome of purely relying on the aircraft measured data is highlighted. It is observed that, with the implementation of adaptive fuzzy logic based extended Kalman filter tuned to adapt for aircraft landing dynamics, the methodology improves the data quality of the states that are sourced from noisy measurements.

Comparison of Carbon Dioxide Airborne Measurement over Land and Ocean using 2-μm Double-Pulse Integrated Path Differential Absorption Lidar

NASA Astrophysics Data System (ADS)

Refaat, T. F.; Singh, U. N.; Petros, M.; Yu, J.; Remus, R.; Ismail, S.

2017-12-01

An airborne Integrated Path Differential Absorption (IPDA) lidar has been developed and validated at NASA Langley Research Center for atmospheric carbon dioxide column measurements. The instrument consists of a tunable, high-energy 2-μm double pulse laser transmitter and 0.4 m telescope receiver coupled to an InGaAs pin detection system. The instrument was validated for carbon dioxide (CO2) measurements from ground and airborne platforms, using a movable lidar trailer and the NASA B-200 aircraft. Airborne validation was conducted over the ocean by comparing the IPDA CO2 optical depth measurement to optical depth model derived using NOAA airborne CO2 air-sampling. Another airborne validation was conducted over land vegetation by comparing the IPDA measurement to a model derived using on-board in-situ measurements using an absolute, non-dispersive infrared gas analyzer (LiCor 840A). IPDA range measurements were also compared to rangefinder and Global Positioning System (GPS) records during ground and airborne validation, respectively. Range measurements from the ground indicated a 0.93 m IPDA range measurement uncertainty, which is limited by the transmitted laser pulse and detection system properties. This uncertainty increased to 2.80 and 7.40 m over ocean and land, due to fluctuations in ocean surface and ground elevations, respectively. IPDA CO2 differential optical depth measurements agree with both models. Consistent CO2 optical depth biases were well correlated with the digitizer full scale input range settings. CO2 optical depth measurements over ocean from 3.1 and 6.1 km altitudes indicated 0.95% and 0.83% uncertainty, respectively, using 10 second (100 shots) averaging. Using the same averaging 0.40% uncertainty was observed over land, from 3.4 km altitude, due to higher surface reflectivity, which increases the return signal power and enhances the signal-to-noise ratio. However, less uncertainty is observed at higher altitudes due to reduced signal shot noise, indicating that detection system noise-equivalent-power dominates the error. These results show that the IPDA technique is well suited for space-based platforms, which includes larger column content integration that enhances the measurement sensitivity.

Be 7 solar neutrino measurement with KamLAND

DOE PAGES

Gando, A.; Gando, Y.; Hanakago, H.; ...

2015-11-30

In this article, we report a measurement of the neutrino-electron elastic scattering rate of 862 keV 7Be solar neutrinos based on a 165.4 kt d exposure of KamLAND. The observed rate is 582 ± 94 (kt d) -1, which corresponds to an 862-keV 7Be solar neutrino flux of (3.26 ± 0.52) × 10 9 cm -2s -1, assuming a pure electron-flavor flux. Comparing this flux with the standard solar model prediction and further assuming three-flavor mixing, a ν e survival probability of 0.66 ± 0.15 is determined from the KamLAND data. Utilizing a global three-flavor oscillation analysis, we obtain amore » total 7Be solar neutrino flux of (5.82 ± 1.02) × 10 9 cm -2s -1, which is consistent with the standard solar model predictions.« less

Be 7 solar neutrino measurement with KamLAND

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

Gando, A.; Gando, Y.; Hanakago, H.

2015-11-30

We report a measurement of the neutrino-electron elastic scattering rate of 862 keV 7Be solar neutrinos based on a 165.4 kt d exposure of KamLAND. The observed rate is 582±94(kt d) ₋1, which corresponds to an 862-keV 7Be solar neutrino flux of (3.26±0.52)×10 9cm ₋2s ₋1, assuming a pure electron-flavor flux. Comparing this flux with the standard solar model prediction and further assuming three-flavor mixing, a ν e survival probability of 0.66±0.15 is determined from the KamLAND data. Lastly, utilizing a global three-flavor oscillation analysis, we obtain a total 7Be solar neutrino flux of (5.82±1.02)×10 9cm ₋2s ₋1, which ismore » consistent with the standard solar model predictions.« less

Spatial distribution of block falls using volumetric GIS-decision-tree models

NASA Astrophysics Data System (ADS)

Abdallah, C.

2010-10-01

Block falls are considered a significant aspect of surficial instability contributing to losses in land and socio-economic aspects through their damaging effects to natural and human environments. This paper predicts and maps the geographic distribution and volumes of block falls in central Lebanon using remote sensing, geographic information systems (GIS) and decision-tree modeling (un-pruned and pruned trees). Eleven terrain parameters (lithology, proximity to fault line, karst type, soil type, distance to drainage line, elevation, slope gradient, slope aspect, slope curvature, land cover/use, and proximity to roads) were generated to statistically explain the occurrence of block falls. The latter were discriminated using SPOT4 satellite imageries, and their dimensions were determined during field surveys. The un-pruned tree model based on all considered parameters explained 86% of the variability in field block fall measurements. Once pruned, it classifies 50% in block falls' volumes by selecting just four parameters (lithology, slope gradient, soil type, and land cover/use). Both tree models (un-pruned and pruned) were converted to quantitative 1:50,000 block falls' maps with different classes; starting from Nil (no block falls) to more than 4000 m 3. These maps are fairly matching with coincidence value equal to 45%; however, both can be used to prioritize the choice of specific zones for further measurement and modeling, as well as for land-use management. The proposed tree models are relatively simple, and may also be applied to other areas (i.e. the choice of un-pruned or pruned model is related to the availability of terrain parameters in a given area).

Advances in Land Data Assimilation at the NASA Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Reichle, Rolf

2009-01-01

Research in land surface data assimilation has grown rapidly over the last decade. In this presentation we provide a brief overview of key research contributions by the NASA Goddard Space Flight Center (GSFC). The GSFC contributions to land assimilation primarily include the continued development and application of the Land Information System (US) and the ensemble Kalman filter (EnKF). In particular, we have developed a method to generate perturbation fields that are correlated in space, time, and across variables and that permit the flexible modeling of errors in land surface models and observations, along with an adaptive filtering approach that estimates observation and model error input parameters. A percentile-based scaling method that addresses soil moisture biases in model and observational estimates opened the path to the successful application of land data assimilation to satellite retrievals of surface soil moisture. Assimilation of AMSR-E surface soil moisture retrievals into the NASA Catchment model provided superior surface and root zone assimilation products (when validated against in situ measurements and compared to the model estimates or satellite observations alone). The multi-model capabilities of US were used to investigate the role of subsurface physics in the assimilation of surface soil moisture observations. Results indicate that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Building on this experience, GSFC leads the development of the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product for the planned NASA Soil-Moisture-Active-Passive (SMAP) mission. A key milestone was the design and execution of an Observing System Simulation Experiment that quantified the contribution of soil moisture retrievals to land data assimilation products as a function of retrieval and land model skill and yielded an estimate of the error budget for the SMAP L4_SM product. Terrestrial water storage observations from GRACE satellite system were also successfully assimilated into the NASA Catchment model and provided improved estimates of groundwater variability when compared to the model estimates alone. Moreover, satellite-based land surface temperature (LST) observations from the ISCCP archive were assimilated using a bias estimation module that was specifically designed for LST assimilation. As with soil moisture, LST assimilation provides modest yet statistically significant improvements when compared to the model or satellite observations alone. To achieve the improvement, however, the LST assimilation algorithm must be adapted to the specific formulation of LST in the land model. An improved method for the assimilation of snow cover observations was also developed. Finally, the coupling of LIS to the mesoscale Weather Research and Forecasting (WRF) model enabled investigations into how the sensitivity of land-atmosphere interactions to the specific choice of planetary boundary layer scheme and land surface model varies across surface moisture regimes, and how it can be quantified and evaluated against observations. The on-going development and integration of land assimilation modules into the Land Information System will enable the use of GSFC software with a variety of land models and make it accessible to the research community.

Land Treatment Research and Development Program, Synthesis of Research Results,

DTIC Science & Technology

1983-08-01

at Pack Forest, Washington .......... 22 8. Infiltration test and the relationship between cumulative water uptake and tim e...the chemistry of phos- phorus in land treatment ..................................... 37 18. Schematic diagram of the compartmental water flow model...39 19. Comparison between predicted and measured water content in slow rate soils .................................................. 39 20

Accessibility-based evaluation of transportation and land-use planning : from laboratory to practice : USDOT Region V Regional University Transportation Center final report.

DOT National Transportation Integrated Search

2016-12-16

The concept of accessibility has made inroads into planning practice, largely at the system level. That is, accessibility is measured or modeled for current or future regional transportation and land-use scenarios for evaluation or broad policy guida...

Land Use/Land Cover Changes and Its Response to Hydrological Characteristics in the Upper Reaches of Minjiang River

NASA Astrophysics Data System (ADS)

Ma, Kai; Huang, Xiaorong; Guo, Biying; Wang, Yanqiu; Gao, Linyun

2018-06-01

Land use changes alter the hydrological characteristics of the land surface, and have significant impacts on hydrological cycle and water balance, the analysis of complex effects on natural systems has become one of the main concerns. In this study, we generated the land use conversion matrixes using ArcGIS and selected several landscape indexes (contagion index, CONTAG, Shannon's diversity index, SHDI, etc.) to evaluate the impact of land use/cover changes on hydrological process in the upper reaches of Minjiang River. We also used a statistical regression model which was established based on hydrology and precipitation data during the period of 1959-2008 to simulate the impacts of different land use conditions on rainfall and runoff in different periods. Our results showed that the simulated annual mean flow from 1985 to 1995 and 1995 to 2008 are 9.19 and 1.04 m3 s-1 lower than the measured values, respectively, which implied that the ecological protection measures should be strengthened in the study area. Our study could provide a scientific basis for water resource management and proper land use planning of upper reaches of Minjiang River.

Optimization of Modeled Land-Atmosphere Exchanges of Water and Energy in an Isotopically-Enabled Land Surface Model by Bayesian Parameter Calibration

NASA Astrophysics Data System (ADS)

Wong, T. E.; Noone, D. C.; Kleiber, W.

2014-12-01

The single largest uncertainty in climate model energy balance is the surface latent heating over tropical land. Furthermore, the partitioning of the total latent heat flux into contributions from surface evaporation and plant transpiration is of great importance, but notoriously poorly constrained. Resolving these issues will require better exploiting information which lies at the interface between observations and advanced modeling tools, both of which are imperfect. There are remarkably few observations which can constrain these fluxes, placing strict requirements on developing statistical methods to maximize the use of limited information to best improve models. Previous work has demonstrated the power of incorporating stable water isotopes into land surface models for further constraining ecosystem processes. We present results from a stable water isotopically-enabled land surface model (iCLM4), including model experiments partitioning the latent heat flux into contributions from plant transpiration and surface evaporation. It is shown that the partitioning results are sensitive to the parameterization of kinetic fractionation used. We discuss and demonstrate an approach to calibrating select model parameters to observational data in a Bayesian estimation framework, requiring Markov Chain Monte Carlo sampling of the posterior distribution, which is shown to constrain uncertain parameters as well as inform relevant values for operational use. Finally, we discuss the application of the estimation scheme to iCLM4, including entropy as a measure of information content and specific challenges which arise in calibration models with a large number of parameters.

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.

Effect of landslides on the structural characteristics of land-cover based on complex networks

NASA Astrophysics Data System (ADS)

He, Jing; Tang, Chuan; Liu, Gang; Li, Weile

2017-09-01

Landslides have been widely studied by geologists. However, previous studies mainly focused on the formation of landslides and never considered the effect of landslides on the structural characteristics of land-cover. Here we define the modeling of the graph topology for the land-cover, using the satellite images of the earth’s surface before and after the earthquake. We find that the land-cover network satisfies the power-law distribution, whether the land-cover contains landslides or not. However, landslides may change some parameters or measures of the structural characteristics of land-cover. The results show that the linear coefficient, modularity and area distribution are all changed after the occurence of landslides, which means the structural characteristics of the land-cover are changed.

Effects of spoilers and gear on B-747 wake vortex velocities

NASA Technical Reports Server (NTRS)

Luebs, A. B.; Bradfute, J. G.; Ciffone, D. L.

1976-01-01

Vortex velocities were measured in the wakes of four configurations of a 0.61-m span model of a B-747 aircraft. The wakes were generated by towing the model underwater in a ship model basin. Tangential and axial velocity profiles were obtained with a scanning laser velocimeter as the wakes aged to 35 span lengths behind the model. A 45 deg deflection of two outboard flight spoilers with the model in the landing configuration resulted in a 36 percent reduction in wake maximum tangential velocity, altered velocity profiles, and erratic vortex trajectories. Deployment of the landing gear with the inboard flaps in the landing position and outboard flaps retracted had little effect on the flap vortices to 35 spans, but caused the wing tip vortices to have: (1) more diffuse velocity profiles; (2) a 27 percent reduction in maximum tangential velocity; and (3) a more rapid merger with the flap vortices.

Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and footprint analysis

NASA Astrophysics Data System (ADS)

Xu, Feinan; Wang, Weizhen; Wang, Jiemin; Xu, Ziwei; Qi, Yuan; Wu, Yueru

2017-08-01

The determination of area-averaged evapotranspiration (ET) at the satellite pixel scale/model grid scale over a heterogeneous land surface plays a significant role in developing and improving the parameterization schemes of the remote sensing based ET estimation models and general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) flux matrix provided a unique opportunity to build an aggregation scheme for area-averaged fluxes. On the basis of the HiWATER flux matrix dataset and high-resolution land-cover map, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. The procedure is as follows. Firstly, quality control and uncertainty estimation for the data of the flux matrix, including 17 eddy-covariance (EC) sites and four groups of large-aperture scintillometers (LASs), were carefully done. Secondly, the representativeness of each EC site was quantitatively evaluated; footprint analysis was also performed for each LAS path. Thirdly, based on the high-resolution land-cover map derived from aircraft remote sensing, a flux aggregation method was established combining footprint analysis and multiple-linear regression. Then, the area-averaged sensible heat fluxes obtained from the EC flux matrix were validated by the LAS measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated. Compared with the formerly used and rather simple approaches, such as the arithmetic average and area-weighted methods, the present scheme is not only with a much better database, but also has a solid grounding in physics and mathematics in the integration of area-averaged fluxes over a heterogeneous surface. Results from this study, both instantaneous and daily ET at the satellite pixel scale, can be used for the validation of relevant remote sensing models and land surface process models. Furthermore, this work will be extended to the water balance study of the whole Heihe River basin.

Which measurement strategies to improve spatial erosion and deposition patterns modelling?

NASA Astrophysics Data System (ADS)

Pineux, Nathalie; Maugnard, Alexandre; Swerts, Gilles; Bielders, Charles; Degré, Aurore

2014-05-01

Validation of the erosion models requires field data. To date, many authors continue to highlight the paucity of accurate field observations and long-term enough studies. The fields observations are often put aside because these measures are difficult to obtain: weighty experimental devices, climatic dependence, … Hence the models are evolving and propose refined calculation procedures including for instance the calculation of landscape evolution. The need of field data therefore increases and new measuring strategies should arise. In the centre of Belgium we choose an agricultural watershed quite representative of the local context. It covers 124 ha of loamy soil with more than 90% of arable land and a weak proportion of forest and artificial lands. The slope ranges between 0 and 9%. Instrumentation on the watershed includes meteorological observations and discharge measurement coupled with water sampling at different outlets. The weather data (radiation, temperature, wind velocity, relative humidity and rainfall) and discharge measurement (comparison between Doppler and pressure sensors) will allow us to model the hydrological behaviour of the catchment. Rainfall readings (tipping buckets) are completed with erosivity readings (disdrometer). Erosivity, together with soil data, land use and agricultural practices observations on field, will be used as entry in the Landsoil model. The sediment samplings at 3 points in the catchment will give an insight of the sediment delivery of 3 subcatchments. The Landsoil model calculates the evolution of the DTM through time. This cannot be compared to measurements at the outlet and requires further data collection. Older elevation data and/or archaeological data are a possible source of information even if their precision remains scarce in our context. 1950's soil surveys are on the contrary really informative since they detail the horizons depth in a spatial way and can be compared to new observation across the watershed. Coupled with unmanned aerial system, they should allow us to test the model performances and improve our knowledge of the spatial patterns of erosion and deposition.

Using plot experiments to test the validity of mass balance models employed to estimate soil redistribution rates from 137Cs and 210Pb(ex) measurements.

PubMed

Porto, Paolo; Walling, Des E

2012-10-01

Information on rates of soil loss from agricultural land is a key requirement for assessing both on-site soil degradation and potential off-site sediment problems. Many models and prediction procedures have been developed to estimate rates of soil loss and soil redistribution as a function of the local topography, hydrometeorology, soil type and land management, but empirical data remain essential for validating and calibrating such models and prediction procedures. Direct measurements using erosion plots are, however, costly and the results obtained relate to a small enclosed area, which may not be representative of the wider landscape. In recent years, the use of fallout radionuclides and more particularly caesium-137 ((137)Cs) and excess lead-210 ((210)Pb(ex)) has been shown to provide a very effective means of documenting rates of soil loss and soil and sediment redistribution in the landscape. Several of the assumptions associated with the theoretical conversion models used with such measurements remain essentially unvalidated. This contribution describes the results of a measurement programme involving five experimental plots located in southern Italy, aimed at validating several of the basic assumptions commonly associated with the use of mass balance models for estimating rates of soil redistribution on cultivated land from (137)Cs and (210)Pb(ex) measurements. Overall, the results confirm the general validity of these assumptions and the importance of taking account of the fate of fresh fallout. However, further work is required to validate the conversion models employed in using fallout radionuclide measurements to document soil redistribution in the landscape and this could usefully direct attention to different environments and to the validation of the final estimates of soil redistribution rate as well as the assumptions of the models employed. Copyright © 2012 Elsevier Ltd. All rights reserved.

What did the Romans ever do for us? Putting humans in global land models

NASA Astrophysics Data System (ADS)

Bierkens, M. F.; Wada, Y.; Dermody, B.; Van Beek, L. P.

2016-12-01

During the late 1980s and early 1990s, awareness of the shortage of global water resources lead to the first detailed global water resources assessments using regional statistics of water use and observations of meteorological and hydrological variables. Shortly thereafter, the first macroscale hydrological models (MHM) appeared. In these models, blue water (i.e., surface water and renewable groundwater) availability was calculated by accumulating runoff over a stream network and comparing it with population densities or with estimated water demand for agriculture, industry and households. In this talk we review the evolution of human impact modelling in global land models with a focus on global water resources, touching upon developments of the last 15 years: i.e. calculating human water scarcity; estimating groundwater depletion; adding dams and reservoirs; fully integrating water use (abstraction, application, consumption, return flow) in the hydrology; simulating the effects of land use change. We identify four major challenges that hamper the further development of integrated water resources modelling and thus prohibit realistic projections of the future terrestrial water cycle in the Anthropocene. These are: 1) including the ability to model infrastructural changes and measures; 2) projecting future water demand and water use and associated measures; 3) including virtual water trade; 4) including land use change and landscape change. While all these challenges will likely benefit from hydro-economics and the newly developing field of socio-hydrology, we also show that especially for challenges 3 and 4 lessons can be drawn from the (pre)historic past. To make this point we provide two case studies: one modelling the virtual water trade in the Roman Empire and one modelling human-landscape interaction in prehistoric Calabria (Italy).

OCO-2 Column Carbon Dioxide and Biometric Data Jointly Constrain Parameterization and Projection of a Global Land Model

NASA Astrophysics Data System (ADS)

Shi, Z.; Crowell, S.; Luo, Y.; Rayner, P. J.; Moore, B., III

2015-12-01

Uncertainty in predicted carbon-climate feedback largely stems from poor parameterization of global land models. However, calibration of global land models with observations has been extremely challenging at least for two reasons. First we lack global data products from systematical measurements of land surface processes. Second, computational demand is insurmountable for estimation of model parameter due to complexity of global land models. In this project, we will use OCO-2 retrievals of dry air mole fraction XCO2 and solar induced fluorescence (SIF) to independently constrain estimation of net ecosystem exchange (NEE) and gross primary production (GPP). The constrained NEE and GPP will be combined with data products of global standing biomass, soil organic carbon and soil respiration to improve the community land model version 4.5 (CLM4.5). Specifically, we will first develop a high fidelity emulator of CLM4.5 according to the matrix representation of the terrestrial carbon cycle. It has been shown that the emulator fully represents the original model and can be effectively used for data assimilation to constrain parameter estimation. We will focus on calibrating those key model parameters (e.g., maximum carboxylation rate, turnover time and transfer coefficients of soil carbon pools, and temperature sensitivity of respiration) for carbon cycle. The Bayesian Markov chain Monte Carlo method (MCMC) will be used to assimilate the global databases into the high fidelity emulator to constrain the model parameters, which will be incorporated back to the original CLM4.5. The calibrated CLM4.5 will be used to make scenario-based projections. In addition, we will conduct observing system simulation experiments (OSSEs) to evaluate how the sampling frequency and length could affect the model constraining and prediction.

Soil erosion risk assessment using interviews, empirical soil erosion modeling (RUSLE) and fallout radionuclides in a volcanic crater lake watershed subjected to land use change, western Uganda

NASA Astrophysics Data System (ADS)

De Crop, Wannes; Ryken, Nick; Tomma Okuonzia, Judith; Van Ranst, Eric; Baert, Geert; Boeckx, Pascal; Verschuren, Dirk; Verdoodt, Ann

2017-04-01

Population pressure results in conversion of natural vegetation to cropland within the western Ugandan crater lake watersheds. These watersheds however are particularly prone to soil degradation and erosion because of the high rainfall intensity and steep topography. Increased soil erosion losses expose the aquatic ecosystems to excessive nutrient loading. In this study, the Katinda crater lake watershed, which is already heavily impacted by agricultural land use, was selected for an explorative study on its (top)soil characteristics - given the general lack of data on soils within these watersheds - as well as an assessment of soil erosion risks. Using group discussions and structured interviews, the local land users' perceptions on land use, soil quality, soil erosion and lake ecology were compiled. Datasets on rainfall, topsoil characteristics, slope gradient and length, and land use were collected. Subsequently a RUSLE erosion model was run. Results from this empirical erosion modeling approach were validated against soil erosion estimates based on 137Cs measurements.

Assessment of Mars Pathfinder landing site predictions

USGS Publications Warehouse

Golombek, M.P.; Moore, H.J.; Haldemann, A.F.C.; Parker, T.J.; Schofield, J.T.

1999-01-01

Remote sensing data at scales of kilometers and an Earth analog were used to accurately predict the characteristics of the Mars Pathfinder landing site at a scale of meters. The surface surrounding the Mars Pathfinder lander in Ares Vallis appears consistent with orbital interpretations, namely, that it would be a rocky plain composed of materials deposited by catastrophic floods. The surface and observed maximum clast size appears similar to predictions based on an analogous surface of the Ephrata Fan in the Channeled Scabland of Washington state. The elevation of the site measured by relatively small footprint delay-Doppler radar is within 100 m of that determined by two-way ranging and Doppler tracking of the spacecraft. The nearly equal elevations of the Mars Pathfinder and Viking Lander 1 sites allowed a prediction of the atmospheric conditions with altitude (pressure, temperature, and winds) that were well within the entry, descent, and landing design margins. High-resolution (~38 m/pixel) Viking Orbiter 1 images showed a sparsely cratered surface with small knobs with relatively low slopes, consistent with observations of these features from the lander. Measured rock abundance is within 10% of that expected from Viking orbiter thermal observations and models. The fractional area covered by large, potentially hazardous rocks observed is similar to that estimated from model rock distributions based on data from the Viking landing sites, Earth analog sites, and total rock abundance. The bulk and fine-component thermal inertias measured from orbit are similar to those calculated from the observed rock size-frequency distribution. A simple radar echo model based on the reflectivity of the soil (estimated from its bulk density), and the measured fraction of area covered by rocks was used to approximate the quasi-specular and diffuse components of the Earth-based radar echos. Color and albedo orbiter data were used to predict the relatively dust free or unweathered surface around the Pathfinder lander compared to the Viking landing sites. Comparisons with the experiences of selecting the Viking landing sites demonstrate the enormous benefit the Viking data and its analyses and models had on the successful predictions of the Pathfinder site. The Pathfinder experience demonstrates that, in certain locations, geologic processes observed in orbiter data can be used to infer surface characteristics where those processes dominate over other processes affecting the Martian surface layer. Copyright 1999 by the American Geophysical Union.

Simulated effects of hydrologic, water quality, and land-use changes of the Lake Maumelle watershed, Arkansas, 2004–10

USGS Publications Warehouse

Hart, Rheannon M.; Green, W. Reed; Westerman, Drew A.; Petersen, James C.; DeLanois, Jeanne L.

2012-01-01

Lake Maumelle, located in central Arkansas northwest of the cities of Little Rock and North Little Rock, is one of two principal drinking-water supplies for the Little Rock, and North Little Rock, Arkansas, metropolitan areas. Lake Maumelle and the Maumelle River (its primary tributary) are more pristine than most other reservoirs and streams in the region with 80 percent of the land area in the entire watershed being forested. However, as the Lake Maumelle watershed becomes increasingly more urbanized and timber harvesting becomes more extensive, concerns about the sustainability of the quality of the water supply also have increased. Two hydrodynamic and water-quality models were developed to examine the hydrology and water quality in the Lake Maumelle watershed and changes that might occur as the watershed becomes more urbanized and timber harvesting becomes more extensive. A Hydrologic Simulation Program–FORTRAN watershed model was developed using continuous streamflow and discreet suspended-sediment and water-quality data collected from January 2004 through 2010. A CE–QUAL–W2 model was developed to simulate reservoir hydrodynamics and selected water-quality characteristics using the simulated output from the Hydrologic Simulation Program–FORTRAN model from January 2004 through 2010. The calibrated Hydrologic Simulation Program–FORTRAN model and the calibrated CE–QUAL–W2 model were developed to simulate three land-use scenarios and to examine the potential effects of these land-use changes, as defined in the model, on the water quality of Lake Maumelle during the 2004 through 2010 simulation period. These scenarios included a scenario that simulated conversion of most land in the watershed to forest (scenario 1), a scenario that simulated conversion of potentially developable land to low-intensity urban land use in part of the watershed (scenario 2), and a scenario that simulated timber harvest in part of the watershed (scenario 3). Simulated land-use changes for scenarios 1 and 3 resulted in little (generally less than 10 percent) overall effect on the simulated water quality in the Hydrologic Simulation Program–FORTRAN model. The land-use change of scenario 2 affected subwatersheds that include Bringle, Reece, and Yount Creek tributaries and most other subwatersheds that drain into the northern side of Lake Maumelle; large percent increases in loading rates (generally between 10 and 25 percent) included dissolved nitrite plus nitrate nitrogen, dissolved orthophosphate, total phosphorus, suspended sediment, dissolved ammonia nitrogen, total organic carbon, and fecal coliform bacteria. For scenario 1, the simulated changes in nutrient, suspended sediment, and total organic carbon loads from the Hydrologic Simulation Program–FORTRAN model resulted in very slight (generally less than 10 percent) changes in simulated water quality for Lake Maumelle, relative to the baseline condition. Following lake mixing in the falls of 2006 and 2007, phosphorus and nitrogen concentrations were higher than the baseline condition and chlorophyll a responded accordingly. The increased nutrient and chlorophyll a concentrations in late October and into 2007 were enough to increase concentrations, on average, for the entire simulation period (2004–10). For scenario 2, the simulated changes in nutrient, suspended sediment, total organic carbon, and fecal coliform bacteria loads from the Lake Maumelle watershed resulted in slight changes in simulated water quality for Lake Maumelle, relative to the baseline condition (total nitrogen decreased by 0.01 milligram per liter; dissolved orthophosphate increased by 0.001 milligram per liter; chlorophyll a decreased by 0.1 microgram per liter). The differences in these concentrations are approximately an order of magnitude less than the error between measured and simulated concentrations in the baseline model. During the driest summer in the simulation period (2006), phosphorus and nitrogen concentrations were lower than the baseline condition and chlorophyll a concentrations decreased during the same summer season. The decrease in nitrogen and chlorophyll a concentrations during the dry summer in 2006 was enough to decrease concentrations of these constituents very slightly, on average, for the entire simulation period (2004–10). For scenario 3, the changes in simulated nutrient, suspended sediment, total organic carbon, and fecal coliform bacteria loads from Lake Maumelle watershed resulted in very slight changes in simulated water quality within Lake Maumelle, relative to the baseline condition, for most of the reservoir. Among the implications of the results of the modeling described in this report are those related to scale in both space and time. Spatial scales include limited size and location of land-use changes, their effects on loading rates, and resultant effects on water quality of Lake Maumelle. Temporally, the magnitude of the water-quality changes simulated by the land-use change scenarios over the 7-year period (2004–10) are not necessarily indicative of the changes that could be expected to occur with similar land-use changes persisting over a 20-, 30-, or 40- year period, for example. These implications should be tempered by realization of the described model limitations. The Hydrologic Simulation Program–FORTRAN watershed model was calibrated to streamflow and water-quality data from five streamflow-gaging stations, and in general, these stations characterize a range of subwatershed areas with varying land-use types. The CE–QUAL–W2 reservoir model was calibrated to water-quality data collected during January 2004 through December 2010 at three reservoir stations, representing the upper, middle, and lower sections of the reservoir. In general, the baseline simulation for the Hydrologic Simulation Program–FORTRAN and the CE–QUAL–W2 models matched reasonably well to the measured data. Simulated and measured suspended-sediment concentrations during periods of base flow (streamflows not substantially influenced by runoff) agree reasonably well for Maumelle River at Williams Junction, the station representing the upper end of the watershed (with differences—simulated minus measured value—generally ranging from -15 to 41 milligrams per liter, and percent difference—relative to the measured value—ranging from -99 to 182 percent) and Maumelle River near Wye, the station just above the reservoir at the lower end (differences generally ranging from -20 to 22 milligrams per liter, and percent difference ranging from -100 to 194 percent). In general, water temperature and dissolved-oxygen concentration simulations followed measured seasonal trends for all stations with the largest differences occurring during periods of lowest temperatures or during the periods of lowest measured dissolved-oxygen concentrations. For the CE–QUAL–W2 model, simulated vertical distributions of water temperatures and dissolved-oxygen concentrations agreed with measured vertical distributions over time, even for the most complex water-temperature profiles. Considering the oligotrophic-mesotrophic (low to intermediate primary productivity and associated low nutrient concentrations) condition of Lake Maumelle, simulated algae, phosphorus, and nitrogen concentrations compared well with generally low measured concentrations.

Nutrient pollution mitigation measures across Europe are resilient under future climate

NASA Astrophysics Data System (ADS)

Wade, Andrew; Skeffington, Richard; Couture, Raoul; Erlandsson, Martin; Groot, Simon; Halliday, Sarah; Harezlak, Valesca; Hejzlar, Joseph; Jackson-Blake, Leah; Lepistö, Ahti; Papastergiadou, Eva; Psaltopoulos, Demetrios; Riera, Joan; Rankinen, Katri; Skuras, Dimitris; Trolle, Dennis; Whitehead, Paul; Dunn, Sarah; Bucak, Tuba

2016-04-01

The key results from the application of catchment-scale biophysical models to assess the likely effectiveness of nutrient pollution mitigation measures set in the context of projected land management and climate change are presented. The assessment is based on the synthesis of modelled outputs of daily river flow, river and lake nitrogen and phosphorus concentrations, and lake chlorophyll-a, for baseline (1981-2010) and scenario (2031-2060) periods for nine study sites across Europe. Together the nine sites represent a sample of key climate and land management types. The robustness and uncertainty in the daily, seasonal and long-term modelled outputs was assessed prior to the scenario runs. Credible scenarios of land-management changes were provided by social scientists and economists familiar with each study site, whilst likely mitigation measures were derived from local stakeholder consultations and cost-effectiveness assessments. Modelled mitigation options were able to reduce nutrient concentrations, and there was no evidence here that they were less effective under future climate. With less certainty, mitigation options could affect the ecological status of waters at these sites in a positive manner, leading to improvement in Water Framework Directive status at some sites. However, modelled outcomes for sites in southern Europe highlighted that increased evaporation and decreased precipitation will cause much lower flows leading to adverse impacts of river and lake ecology. Uncertainties in the climate models, as represented by three GCM-RCM combinations, did not affect this overall picture much.

Crowd-Sourcing Management Activity Data to Drive GHG Emission Inventories in the Land Use Sector

NASA Astrophysics Data System (ADS)

Paustian, K.; Herrick, J.

2015-12-01

Greenhouse gas (GHG) emissions from the land use sector constitute the largest source category for many countries in Africa. Enhancing C sequestration and reducing GHG emissions on managed lands in Africa has to potential to attract C financing to support adoption of more sustainable land management practices that, in addition to GHG mitigation, can provide co-benefits of more productive and climate-resilient agroecosystems. However, robust systems to measure and monitor C sequestration/GHG reductions are currently a significant barrier to attracting more C financing to land use-related mitigation efforts.Anthropogenic GHG emissions are driven by a variety of environmental factors, including climate and soil attributes, as well as human-activities in the form of land use and management practices. GHG emission inventories typically use empirical or process-based models of emission rates that are driven by environmental and management variables. While a lack of field-based flux and C stock measurements are a limiting factor for GHG estimation, we argue that an even greater limitation may be availabiity of data on the management activities that influence flux rates, particularly in developing countries in Africa. In most developed countries there is a well-developed infrastructure of agricultural statistics and practice surveys that can be used to drive model-based GHG emission estimations. However, this infrastructure is largely lacking in developing countries in Africa. While some activity data (e.g. land cover change) can be derived from remote sensing, many key data (e.g., N fertilizer practices, residue management, manuring) require input from the farmers themselves. The explosive growth in cellular technology, even in many of the poorest parts of Africa, suggests the potential for a new crowd-sourcing approach and direct engagement with farmers to 'leap-frog' the land resource information model of developed countries. Among the many benefits of this approach would be high resolution management data to support GHG inventories at multiple scales. We present an overall conceptual model for this approach and examples from on-going projects in Africa employing direct farmer engagement, cellular technology and apps to develop this information resource.

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.

Integration of satellite-induced fluorescence and vegetation optical depth to improve the retrieval of land evaporation

NASA Astrophysics Data System (ADS)

Pagán, B. R.; Martens, B.; Maes, W. H.; Miralles, D. G.

2017-12-01

Global satellite-based data sets of land evaporation overcome limitations in coverage of in situ measurements while retaining some observational nature. Although their potential for real world applications are promising, their value during dry conditions is still poorly understood. Most evaporation retrieval algorithms are not directly sensitive to soil moisture. An exception is the Global Land Evaporation Amsterdam Model (GLEAM), which uses satellite surface soil moisture and precipitation to account for land water availability. The existing methodology may greatly benefit from the optimal integration of novel observations of the land surface. Microwave vegetation optical depth (VOD) and near-infrared solar-induced fluorescence (SIF) are expected to reflect different aspects of evaporative stress. While the former is considered to be a proxy of vegetation water content, the latter is indicative of the activity of photosynthetic machinery. As stomata regulate both photosynthesis and transpiration, we expect a relationship between SIF and transpiration. An important motivation to incorporate observations in land evaporation calculations is that plant transpiration - usually the largest component of the flux - is extremely challenging to model due to species-dependent responses to drought. Here we present an innovative integration of VOD and SIF into the GLEAM evaporative stress function. VOD is utilized as a measurement of isohydricity to improve the representation of species specific drought responses. SIF is used for transpiration modelling, a novel application, and standardized by incoming solar radiation to better account for radiation-limited periods. Results are validated with global FLUXNET and International Soil Moisture Network data and demonstrate that the incorporation of VOD and SIF can yield accurate estimates of transpiration over large-scales, which are essential to further understand ecosystem-atmosphere feedbacks and the response of terrestrial hydrology and ecology to meteorological drought. The resulting retrievals of land evaporation can be used to benchmark climate model representation of turbulent fluxes, at a time when these models still consider water stress rudimentarily, and typically assume the same sensitivity for all vegetation types to drought stress.

Magnetism and the interior of the moon. [measured at Apollo landing sites

NASA Technical Reports Server (NTRS)

Dyal, P.; Parkin, C. W.; Daily, W. D.

1974-01-01

During the time period 1961-1972 eleven magnetometers were sent to the moon. The results of lunar magnetometer data analysis are reviewed, with emphasis on the lunar interior. Magnetic fields have been measured on the lunar surface at the Apollo 12, 14, 15, and 16 landing sites. The remanent field values at these sites are given. Satellite and surface measurements show strong evidence that the lunar crust is magnetized over much of the lunar globe. The origin of the lunar remanent field is not yet satisfactorily understood; several source models are presented. Simultaneous data from the Apollo 12 lunar surface magnetometer and the Explorer 35 Ames magnetometer are used to construct a wholemoon hysteresis curve, from which the global lunar permeability is determined. Total iron abundance is calculated for two assumed compositional models of the lunar interior. Other lunar models with a small iron core and with a shallow iron-rich layer are also discussed in light of the measured global permeability.

Assessment of human thermal comfort and mitigation measures in different urban climatotopes

NASA Astrophysics Data System (ADS)

Müller, N.; Kuttler, W.

2012-04-01

This study analyses thermal comfort in the model city of Oberhausen as an example for the densely populated metropolitan region Ruhr, Germany. As thermal loads increase due to climate change negative impacts especially for city dwellers will arise. Therefore mitigation strategies should be developed and considered in urban planning today to prevent future thermal stress. The method consists of the combination of in-situ measurements and numerical model simulations. So in a first step the actual thermal situation is determined and then possible mitigation strategies are derived. A measuring network was installed in eight climatotopes for a one year period recording air temperature, relative humidity, wind speed and wind direction. Based on these parameters the human thermal comfort in terms of physiological equivalent temperature (PET) was calculated by RayMan Pro software. Thus the human comfort of different climatotopes was determined. Heat stress in different land uses varies, so excess thermal loads in urban areas could be detected. Based on the measuring results mitigation strategies were developed, such as increasing areas with high evaporation capacity (green areas and water bodies). These strategies were implemented as different plan scenarios in the microscale urban climate model ENVI-met. The best measure should be identified by comparing the range and effect of these scenarios. Simulations were run in three of the eight climatotopes (city center, suburban and open land site) to analyse the effectiveness of the mitigation strategies in several land use structures. These cover the range of values of all eight climatotopes and therefore provide representative results. In the model area of 21 ha total, the modified section in the different plan scenarios was 1 ha. Thus the effect of small-scale changes could be analysed. Such areas can arise due to population decline and structural changes and hold conversion potential. Emphasis was also laid on analysing the effectiveness of water bodies, which need further research in contrast to well analysed vegetation areas. Results show different thermal loads in the miscellaneous climatotopes due to land use structures. Both measurements and model simulations demonstrate the positive effect on thermal comfort due to augmentation of areas with high evaporation capacity. These effects can be especially well detected in summer, when heat stress is most pronounced. The measurement based PET calculations show a maximum difference of 4 K PET between inner city and open land site in summer nights. Simulation results overall present a PET reduction of 1-3 K. The average PET reduction in the city center site is about 2 K, while the maximum reduction in the suburban site can exceed 5 K. In urban areas parks are particularly advisable as mitigation measure, because they reduce thermal stress both by tree shading and evapotranspiration.

Estimation of Ecosystem Parameters of the Community Land Model with DREAM: Evaluation of the Potential for Upscaling Net Ecosystem Exchange

NASA Astrophysics Data System (ADS)

Hendricks Franssen, H. J.; Post, H.; Vrugt, J. A.; Fox, A. M.; Baatz, R.; Kumbhar, P.; Vereecken, H.

2015-12-01

Estimation of net ecosystem exchange (NEE) by land surface models is strongly affected by uncertain ecosystem parameters and initial conditions. A possible approach is the estimation of plant functional type (PFT) specific parameters for sites with measurement data like NEE and application of the parameters at other sites with the same PFT and no measurements. This upscaling strategy was evaluated in this work for sites in Germany and France. Ecosystem parameters and initial conditions were estimated with NEE-time series of one year length, or a time series of only one season. The DREAM(zs) algorithm was used for the estimation of parameters and initial conditions. DREAM(zs) is not limited to Gaussian distributions and can condition to large time series of measurement data simultaneously. DREAM(zs) was used in combination with the Community Land Model (CLM) v4.5. Parameter estimates were evaluated by model predictions at the same site for an independent verification period. In addition, the parameter estimates were evaluated at other, independent sites situated >500km away with the same PFT. The main conclusions are: i) simulations with estimated parameters reproduced better the NEE measurement data in the verification periods, including the annual NEE-sum (23% improvement), annual NEE-cycle and average diurnal NEE course (error reduction by factor 1,6); ii) estimated parameters based on seasonal NEE-data outperformed estimated parameters based on yearly data; iii) in addition, those seasonal parameters were often also significantly different from their yearly equivalents; iv) estimated parameters were significantly different if initial conditions were estimated together with the parameters. We conclude that estimated PFT-specific parameters improve land surface model predictions significantly at independent verification sites and for independent verification periods so that their potential for upscaling is demonstrated. However, simulation results also indicate that possibly the estimated parameters mask other model errors. This would imply that their application at climatic time scales would not improve model predictions. A central question is whether the integration of many different data streams (e.g., biomass, remotely sensed LAI) could solve the problems indicated here.

An inexact risk management model for agricultural land-use planning under water shortage

NASA Astrophysics Data System (ADS)

Li, Wei; Feng, Changchun; Dai, Chao; Li, Yongping; Li, Chunhui; Liu, Ming

2016-09-01

Water resources availability has a significant impact on agricultural land-use planning, especially in a water shortage area such as North China. The random nature of available water resources and other uncertainties in an agricultural system present risk for land-use planning and may lead to undesirable decisions or potential economic loss. In this study, an inexact risk management model (IRM) was developed for supporting agricultural land-use planning and risk analysis under water shortage. The IRM model was formulated through incorporating a conditional value-at-risk (CVaR) constraint into an inexact two-stage stochastic programming (ITSP) framework, and could be used to control uncertainties expressed as not only probability distributions but also as discrete intervals. The measure of risk about the second-stage penalty cost was incorporated into the model so that the trade-off between system benefit and extreme expected loss could be analyzed. The developed model was applied to a case study in the Zhangweinan River Basin, a typical agricultural region facing serious water shortage in North China. Solutions of the IRM model showed that the obtained first-stage land-use target values could be used to reflect decision-makers' opinions on the long-term development plan. The confidence level α and maximum acceptable risk loss β could be used to reflect decisionmakers' preference towards system benefit and risk control. The results indicated that the IRM model was useful for reflecting the decision-makers' attitudes toward risk aversion and could help seek cost-effective agricultural land-use planning strategies under complex uncertainties.

Development of Forest Drought Index and Forest Water Use Prediction in Gyeonggi Province, Korea Using High-Resolution Weather Research and Forecast Data and Localized JULES Land Surface Model

NASA Astrophysics Data System (ADS)

Lee, H.; Park, J.; Cho, S.; Lee, S. J.; Kim, H. S.

2017-12-01

Forest determines the amount of water available to low land ecosystems, which use the rest of water after evapotranspiration by forests. Substantial increase of drought, especially for seasonal drought, has occurred in Korea due to climate change, recently. To cope with this increasing crisis, it is necessary to predict the water use of forest. In our study, forest water use in the Gyeonggi Province in Korea was estimated using high-resolution (spatial and temporal) meteorological forecast data and localized Joint UK Land Environment Simulator (JULES) which is one of the widely used land surface models. The modeled estimation was used for developing forest drought index. The localization of the model was conducted by 1) refining the existing two tree plant functional types (coniferous and deciduous trees) into five (Quercus spp., other deciduous tree spp., Pinus spp., Larix spp., and other coniferous spp.), 2) correcting moderate resolution imaging spectroradiometer (MODIS) leaf area index (LAI) through data assimilation with in situ measured LAI, and 3) optimizing the unmeasured plant physiological parameters (e.g. leaf nitrogen contents, nitrogen distribution within canopy, light use efficiency) based on sensitivity analysis of model output values. The high-resolution (hourly and 810 × 810 m) National Center for AgroMeteorology-Land-Atmosphere Modeling Package (NCAM-LAMP) data were employed as meteorological input data in JULES. The plant functional types and soil texture of each grid cell in the same resolution with that of NCAM-LAMP was also used. The performance of the localized model in estimating forest water use was verified by comparison with the multi-year sapflow measurements and Eddy covariance data of Taehwa Mountain site. Our result can be used as referential information to estimate the forest water use change by the climate change. Moreover, the drought index can be used to foresee the drought condition and prepare to it.

Simulation on Change Law of Runoff, Sediment and Non-point Source Nitrogen and Phosphorus Discharge under Different Land uses Based on SWAT Model: A Case Study of Er hai Lake Small Watershed

NASA Astrophysics Data System (ADS)

Tong, Xiao Xia; Lai Cui, Yuan; Chen, Man Yu; Hu, Bo; Xu, Wen Sheng

2018-05-01

The Er yuan watershed of Er hai district is chosen as the research area, the law of runoff and sediment and non-point source nitrogen and phosphorus discharges under different land uses during 2001 to 2014 are simulated based on SWAT model. Results of simulation indicate that the order of total runoff yield of different land use type from high to low is grassland, paddy fields, dry land. Specifically, the order of surface runoff yield from high to low is paddy fields, dry land, grassland, the order of lateral runoff yield from high to low is paddy fields, dry land, grassland, the order of groundwater runoff yield from high to low is grassland, paddy fields, dry land. The orders of sediment and nitrogen and phosphorus yield per unit area of different land use type are the same, grassland> paddy fields> dry land. It can be seen, nitrogen and phosphorus discharges from paddy fields and dry land are the main sources of agricultural non-point pollution of the irrigated area. Therefore, reasonable field management measures which can decrease the discharge of nitrogen and phosphorus of paddy fields and dry land are the key to agricultural non-point source pollution prevention and control.

Landing Characteristics of a Lenticular-Shaped Reentry Vehicle

NASA Technical Reports Server (NTRS)

Blanchard, Ulysse J.

1961-01-01

An experimental investigation was made of the landing characteristics of a 1/9-scale dynamic model of a lenticular-shaped reentry vehicle having extendible tail panels for control after reentry and for landing control (flare-out). The landing tests were made by catapulting a free model onto a hard-surface runway and onto water. A "belly-landing" technique in which the vehicle was caused to skid and rock on its curved undersurface (heat shield), converting sinking speed into angular energy, was investigated on a hard-surface runway. Landings were made in calm water and in waves both with and without auxiliary landing devices. Landing motions and acceleration data were obtained over a range of landing attitudes and initial sinking speeds during hard-surface landings and for several wave conditions during water landings. A few vertical landings (parachute letdown) were made in calm water. The hard-surface landing characteristics were good. Maximum landing accelerations on a hard surface were 5g and 18 radians per sq second over a range of landing conditions. Horizontal landings on water resulted in large violent rebounds and some diving in waves. Extreme attitude changes during rebound at initial impact made the attitude of subsequent impact random. Maximum accelerations for water landings were approximately 21g and 145 radians per sq second in waves 7 feet high. Various auxiliary water-landing devices produced no practical improvement in behavior. Reduction of horizontal speed and positive control of impact attitude did improve performance in calm water. During vertical landings in calm water maximum accelerations of 15g and 110 radians per sq second were measured for a contact attitude of -45 deg and a vertical velocity of 70 feet per second.

WIND VELOCITIES AND SAND FLUXES IN MESQUITE DUNE-LANDS IN THE NORTHERN CHIHUAHUAN DESERT: A COMPARISON BETWEEN FIELD MEASUREMENTS AND THE QUIC (QUICK URBAN AND INDUSTRIAL COMPLEX) MODEL

EPA Science Inventory

The poster shows comparisons of wind velocities and sand fluxes between field measurements and a computer model, called QUIC (Quick Urban & Industrial Complex). The comparisons were made for a small desert region in New Mexico.

The Cold Land Processes Experiment (CLPX-1): Analysis and Modelling of LSOS Data (IOP3 Period)

NASA Technical Reports Server (NTRS)

Tedesco, Marco; Kim, Edward J.; Cline, Don; Graf, Tobias; Koike, Toshio; Hardy, Janet; Armstrong, Richard; Brodzik, Mary

2004-01-01

Microwave brightness temperatures at 18.7,36.5, and 89 GHz collected at the Local-Scale Observation Site (LSOS) of the NASA Cold-Land Processes Field Experiment in February, 2003 (third Intensive Observation Period) were simulated using a Dense Media Radiative Transfer model (DMRT), based on the Quasi Crystalline Approximation with Coherent Potential (QCA-CP). Inputs to the model were averaged from LSOS snow pit measurements, although different averages were used for the lower frequencies vs. the highest one, due to the different penetration depths and to the stratigraphy of the snowpack. Mean snow particle radius was computed as a best-fit parameter. Results show that the model was able to reproduce satisfactorily brightness temperatures measured by the University of Tokyo s Ground Based Microwave Radiometer system (CBMR-7). The values of the best-fit snow particle radii were found to fall within the range of values obtained by averaging the field-measured mean particle sizes for the three classes of Small, Medium and Large grain sizes measured at the LSOS site.

In situ optical measurements of Chang'E-3 landing site in Mare Imbrium: 2. Photometric properties of the regolith

NASA Astrophysics Data System (ADS)

Jin, Weidong; Zhang, Hao; Yuan, Ye; Yang, Yazhou; Shkuratov, Yuriy G.; Lucey, Paul G.; Kaydash, Vadim G.; Zhu, Meng-Hua; Xue, Bin; Di, Kaichang; Xu, Bin; Wan, Wenhui; Xiao, Long; Wang, Ziwei

2015-10-01

The panorama cameras onboard the Yutu Rover of the Chang'E-3 lunar mission acquired hundreds of high-resolution color images of the lunar surface and captured the first in situ lunar opposition effect (OE) since the Apollo era. We extracted the phase curve and the color ratio in three bands with the phase angle range from 2° to 141°. Photometric inversions using the Hapke model reveal that submicroscopic dusts are present in the landing area and both the coherent backscattering and the shadow hiding are responsible for the strong OE. Compared with spaceborne measurements, the grains in the landing site are brighter, more transparent, and appear to be better crystallized than the average maria basaltic grains. The results show that the phase-reddening effect appears to be present in the in situ phase curves. The current phase curve can be used as the ground-truth validations of any future spaceborne phase curve measurement over the landing site region.

NASA MEaSUREs Combined ASTER and MODIS Emissivity over Land (CAMEL)

NASA Astrophysics Data System (ADS)

Borbas, E. E.; Hulley, G. C.; Feltz, M.; Knuteson, R. O.; Hook, S. J.

2016-12-01

A land surface emissivity product of the NASA MEASUREs project called Combined ASTER and MODIS Emissivity over Land (CAMEL) is being made available as part of the Unified and Coherent Land Surface Temperature and Emissivity (LST&E) Earth System Data Record (ESDR). The CAMEL database has been created by merging the UW MODIS-based baseline-fit emissivity database (UWIREMIS) developed at the University of Wisconsin-Madison, and the ASTER Global Emissivity Database (ASTER GED V4) produced at JPL. This poster will introduce the beta version of the database, which is available globally for the period 2003 through 2015 at 5km in mean monthly time-steps and for 13 bands from 3.6-14.3 micron. An algorithm to create a high spectral emissivity on 417 wavenumbers is also provided for high spectral IR applications. On the poster the CAMEL database has been evaluated with the IASI Emissivity Atlas (Zhou et al, 2010) and laboratory measurements, and also through simulation of IASI BTs in the RTTOV Forward model.

Modeling suspended sediment sources and transport in the Ishikari River basin, Japan, using SPARROW

NASA Astrophysics Data System (ADS)

Duan, W. L.; He, B.; Takara, K.; Luo, P. P.; Nover, D.; Hu, M. C.

2015-03-01

It is important to understand the mechanisms that control the fate and transport of suspended sediment (SS) in rivers, because high suspended sediment loads have significant impacts on riverine hydroecology. In this study, the SPARROW (SPAtially Referenced Regression on Watershed Attributes) watershed model was applied to estimate the sources and transport of SS in surface waters of the Ishikari River basin (14 330 km2), the largest watershed in Hokkaido, Japan. The final developed SPARROW model has four source variables (developing lands, forest lands, agricultural lands, and stream channels), three landscape delivery variables (slope, soil permeability, and precipitation), two in-stream loss coefficients, including small streams (streams with drainage area < 200 km2) and large streams, and reservoir attenuation. The model was calibrated using measurements of SS from 31 monitoring sites of mixed spatial data on topography, soils and stream hydrography. Calibration results explain approximately 96% (R2) of the spatial variability in the natural logarithm mean annual SS flux (kg yr-1) and display relatively small prediction errors at the 31 monitoring stations. Results show that developing land is associated with the largest sediment yield at around 1006 kg km-2 yr-1, followed by agricultural land (234 kg km-2 yr-1). Estimation of incremental yields shows that 35% comes from agricultural lands, 23% from forested lands, 23% from developing lands, and 19% from stream channels. The results of this study improve our understanding of sediment production and transportation in the Ishikari River basin in general, which will benefit both the scientific and management communities in safeguarding water resources.

Soil mapping and processes modelling for sustainable land management: a review

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Brevik, Eric; Muñoz-Rojas, Miriam; Miller, Bradley; Smetanova, Anna; Depellegrin, Daniel; Misiune, Ieva; Novara, Agata; Cerda, Artemi

2017-04-01

Soil maps and models are fundamental for a correct and sustainable land management (Pereira et al., 2017). They are an important in the assessment of the territory and implementation of sustainable measures in urban areas, agriculture, forests, ecosystem services, among others. Soil maps represent an important basis for the evaluation and restoration of degraded areas, an important issue for our society, as consequence of climate change and the increasing pressure of humans on the ecosystems (Brevik et al. 2016; Depellegrin et al., 2016). The understanding of soil spatial variability and the phenomena that influence this dynamic is crucial to the implementation of sustainable practices that prevent degradation, and decrease the economic costs of soil restoration. In this context, soil maps and models are important to identify areas affected by degradation and optimize the resources available to restore them. Overall, soil data alone or integrated with data from other sciences, is an important part of sustainable land management. This information is extremely important land managers and decision maker's implements sustainable land management policies. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. References Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. (2016) Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274. Depellegrin, D.A., Pereira, P., Misiune, I., Egarter-Vigl, L. (2016) Mapping Ecosystem Services in Lithuania. International Journal of Sustainable Development and World Ecology, 23, 441-455. Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B., Smetanova, A., Depellegrin, D., Misiune, I., Novara, A., Cerda, A. (2017) Soil mapping and process modelling for sustainable land management. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

Improving predictions of the effects of extreme events, land use, and climate change on the hydrology of watersheds in the Philippines

NASA Astrophysics Data System (ADS)

Benavidez, Rubianca; Jackson, Bethanna; Maxwell, Deborah; Paringit, Enrico

2016-05-01

Due to its location within the typhoon belt, the Philippines is vulnerable to tropical cyclones that can cause destructive floods. Climate change is likely to exacerbate these risks through increases in tropical cyclone frequency and intensity. To protect populations and infrastructure, disaster risk management in the Philippines focuses on real-time flood forecasting and structural measures such as dikes and retaining walls. Real-time flood forecasting in the Philippines mostly utilises two models from the Hydrologic Engineering Center (HEC): the Hydrologic Modeling System (HMS) for watershed modelling, and the River Analysis System (RAS) for inundation modelling. This research focuses on using non-structural measures for flood mitigation, such as changing land use management or watershed rehabilitation. This is being done by parameterising and applying the Land Utilisation and Capability Indicator (LUCI) model to the Cagayan de Oro watershed (1400 km2) in southern Philippines. The LUCI model is capable of identifying areas providing ecosystem services such as flood mitigation and agricultural productivity, and analysing trade-offs between services. It can also assess whether management interventions could enhance or degrade ecosystem services at fine spatial scales. The LUCI model was used to identify areas within the watershed that are providing flood mitigating services and areas that would benefit from management interventions. For the preliminary comparison, LUCI and HEC-HMS were run under the same scenario: baseline land use and the extreme rainfall event of Typhoon Bopha. The hydrographs from both models were then input to HEC-RAS to produce inundation maps. The novelty of this research is two-fold: (1) this type of ecosystem service modelling has not been carried out in the Cagayan de Oro watershed; and (2) this is the first application of the LUCI model in the Philippines. Since this research is still ongoing, the results presented in this paper are preliminary. As the land use and soil parameterisation for this watershed are refined and more scenarios are run through the model, more robust comparisons can be made between the hydrographs produced by LUCI and HEC-HMS and how those differences affect the inundation map produced by HEC-RAS.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Local and Long-Distance Effects of Land Use Change on Nutrient Levels in Streams and Rivers of the Conterminous United States

NASA Astrophysics Data System (ADS)

Smith, R. A.; Alexander, R. B.; Schwarz, G. E.

2003-12-01

Determining the effects of land use change (e.g. urbanization, deforestation) on water quality at large spatial scales has been difficult because water quality measurements in large rivers with heterogeneous basins show the integrated effects of multiple factors. Moreover, the observed effects of land use changes on water quality in small homogeneous stream basins may not be indicative of downstream effects (including effects on such ecologically relevant characteristics as nutrient levels and elemental ratios) because of loss processes occurring during downstream transport in river channels. In this study we used the USGS SPARROW (Spatially-Referenced Regression on Watersheds) models of total nitrogen (TN) and total phosphorus (TP) in streams and rivers of the conterminous US to examine the effects of various aspects of land use change on nutrient concentrations and flux from the pre-development era to the present. The models were calibrated with data from 370 long-term monitoring stations representing a wide range of basin sizes, land use/cover classes, climates, and physiographies. The non-linear formulation for each model includes 20+ statistically estimated parameters relating to land use/cover characteristics and other environmental variables such as temperature, soil conditions, hill slope, and the hydraulic characteristics of 2200 large lakes and reservoirs. Model predictions are available for 62,000 river/stream channel nodes. Model predictions of pre-development water quality compare favorably with nutrient data from 63 undeveloped (reference) sites. Error statistics are available for predictions at all nodes. Model simulations were chosen to compare the effects of selected aspects of land use change on nutrient levels at large and small basin scales, lacustrine and coastal receiving waters, and among the major US geographic regions.

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

Zhao, Chun; Huang, Maoyi; Fast, Jerome D.

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model withmore » chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.« less

Measurement of Martian boundary layer winds by the displacement of jettisoned lander hardware

NASA Astrophysics Data System (ADS)

Paton, M. D.; Harri, A.-M.; Savijärvi, H.

2018-07-01

Martian boundary layer wind speed and direction measurements, from a variety of locations, seasons and times, are provided. For each lander sent to Mars over the last four decades a unique record of the winds blowing during their descent is preserved at each landing site. By comparing images acquired from orbiting spacecraft of the impact points of jettisoned hardware, such as heat shields and parachutes, to a trajectory model the winds can be measured. We start our investigations with the Viking lander 1 mission and end with Schiaparelli. In-between we extract wind measurements based on observations of the Beagle 2, Spirit, Opportunity, Phoenix and Curiosity landing sites. With one exception the wind at each site during the lander's descent were found to be < 8 m s-1. High speed winds were required to explain the displacement of jettisoned hardware at the Phoenix landing site. We found a tail wind ( > 20 m s-1), blowing from the north-west was required at a high altitude ( > 2 km) together with a gust close to the surface ( < 500 m altitude) originating from the north. All in all our investigations yielded a total of ten unique wind measurements in the PBL. One each from the Viking landers and one each from Beagle 2, Spirit, Opportunity and Schiaparelli. Two wind measurements, one above about 1 km altitude and one below, were possible from observations of the Curiosity and Phoenix landing site. Our findings are consistent with a turbulent PBL in the afternoon and calm PBL in the morning. When comparing our results to a GCM we found a good match in wind direction but not for wind speed. The information provided here makes available wind measurements previously unavailable to Mars atmosphere modellers and investigators.

Investigation of Skylab imagery for regional planning. [New York, New Jersey, and Connecticut

NASA Technical Reports Server (NTRS)

Harting, W. (Principal Investigator)

1975-01-01

The author has identified the following significant results. It is feasible to use earth terrain camera imagery to detect four land uses (vacant land, developed land, streets, and water) for general regional planning purposes. Multispectral imagery is suitable for detecting, mapping, and measuring water bodies as small as two acres. Sufficient information can be extracted to prepare graphic and pictorial representations of the general growth and development patterns, but cannot be incorporated into an inventory file for predictive models.

How well do we succeed in modeling the global soil carbon pools?

NASA Astrophysics Data System (ADS)

Viskari, T.; Liski, J.

2017-12-01

Terrestrial carbon pools are a crucial part of the global carbon cycle. Carbon from vegetation is deposited to the soil, which in turn releases carbon dioxide back to the atmosphere through heterotrophic respiration. The resulting soil carbon storage in the largest on land. While there are continuous efforts to improve the modeling of global soil carbon and how this storage is affected by climate change, this research requires still a more reliable baseline on how well the models estimate the current global soil carbon pools. Especially such comparisons are important for identifying the major challenges in the current soil carbon models. Here, we used the Yasso soil carbon model to create a global soil carbon map at a 0.5 degree resolution based on the available climate, land cover and vegetation productivity information. Yasso model describes the soil carbon cycling by pools that represent the breaking down of dead organic matter. We compared the model results to a measurement based projection of global soil carbon pools, and we examined the differences and spatial correlations between the two maps. In our findings, the modelled predictions captured the overall soil carbon distributions within 5 kgCm-2 on 63 % of the land area. The spatial distributions fit each other as well. The average soil carbon is smaller with the Yasso prediction ( 8.5 kg m-2) than with the measurement map ( 10 kg m-2) and there are notable areas, such as Siberia and Southern North America, where there are large differences between the model predictions and measurements. These results not only encourage future development of soil carbon models, but also highlight problem areas to focus and improve upon.

Coupled land surface/hydrologic/atmospheric models

NASA Technical Reports Server (NTRS)

Pielke, Roger; Steyaert, Lou; Arritt, Ray; Lahtakia, Mercedes; Smith, Chris; Ziegler, Conrad; Soong, Su Tzai; Avissar, Roni; Wetzel, Peter; Sellers, Piers

1993-01-01

The topics covered include the following: prototype land cover characteristics data base for the conterminous United States; surface evapotranspiration effects on cumulus convection and implications for mesoscale models; the use of complex treatment of surface hydrology and thermodynamics within a mesoscale model and some related issues; initialization of soil-water content for regional-scale atmospheric prediction models; impact of surface properties on dryline and MCS evolution; a numerical simulation of heavy precipitation over the complex topography of California; representing mesoscale fluxes induced by landscape discontinuities in global climate models; emphasizing the role of subgrid-scale heterogeneity in surface-air interaction; and problems with modeling and measuring biosphere-atmosphere exchanges of energy, water, and carbon on large scales.

Monitoring landscape level processes using remote sensing of large plots

Treesearch

Raymond L. Czaplewski

1991-01-01

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

Titan Ground Complex Permittivity at the HUYGENS Landing Site; the PWA-HASI and Other Instruments Data Revisited

NASA Astrophysics Data System (ADS)

Hamelin, M.; Lethuillier, A.; Le Gall, A. A.; Grard, R.; Ciarletti, V.; Béghin, C.; Schwingenschuh, K.; Lorenz, R. D.; Lopez-Moreno, J. J.; Jernej, I.; Brown, V.; Ferri, F.

2014-12-01

Ten years after the successful landing of the HUYGENS probe on the surface of Titan, we reassess the complex permittivity measurements of the surface materials performed by the PWA-HASI experiment (Permittivity, Waves and Altimetry - Huygens Atmospheric Structure Instrument). The complex permittivity is inferred from the mutual impedance of a classical quadrupolar probe, ie. the ratio of the voltage measured by a receiving dipole over the current emitted by another dipole. Using a simple model of the quadrupole configuration, the dielectric constant of the material at the landing site was first estimated to be of the order of 1.8. A more realistic numerical model that took into account the influence of the HUYGENS gondola yielded a dielectric constant in the range 2-3 and a conductivity in the range 0.4 - 0.8 nS/m. due to uncertainties about the system geometry ( Grard et al., 2006). However, a puzzling experimental fact remains to be explained, namely a sudden variation of the amplitude and phase of the received voltage 11 mn after landing that cannot be associated with any lander mechanical disturbance. Permittivity estimations were based on the first 11 mn sequence. The present analysis takes advantage of a recent analysis of the landing process that provided more realistic final position and attitude for the HUYGENS lander (Schroder et al., 2012). The new results lie within former estimated ranges and attention is paid to their sensitivity to geometry and to the reference measurements collected immediately before landing. This point is particularly critical for the estimation of the conductivity. The complete data set has been analysed, including the sequence collected after the first 11 mn. We consider various scenarios that may explain the observed phase and amplitude discontinuity. We tested two layers ground models in order to investigate the possibility that the upper layer may have experienced a fast physical change due to deliquescence or outgasing. Unfortunately a rigid quadrupolar array measure the average electric properties of the ground and cannot detect any inhomogeneity. We present in addition the measurements made last May in the Dachstein ice cave in Austria, with a mockup of HUYGENS-PWA and a replica of the PP-SESAME instrument onboard the PHILAE lander of ROSETTA

Land-use regression panel models of NO2 concentrations in Seoul, Korea

NASA Astrophysics Data System (ADS)

Kim, Youngkook; Guldmann, Jean-Michel

2015-04-01

Transportation and land-use activities are major air pollution contributors. Since their shares of emissions vary across space and time, so do air pollution concentrations. Despite these variations, panel data have rarely been used in land-use regression (LUR) modeling of air pollution. In addition, the complex interactions between traffic flows, land uses, and meteorological variables, have not been satisfactorily investigated in LUR models. The purpose of this research is to develop and estimate nitrogen dioxide (NO2) panel models based on the LUR framework with data for Seoul, Korea, accounting for the impacts of these variables, and their interactions with spatial and temporal dummy variables. The panel data vary over several scales: daily (24 h), seasonally (4), and spatially (34 intra-urban measurement locations). To enhance model explanatory power, wind direction and distance decay effects are accounted for. The results show that vehicle-kilometers-traveled (VKT) and solar radiation have statistically strong positive and negative impacts on NO2 concentrations across the four seasonal models. In addition, there are significant interactions with the dummy variables, pointing to VKT and solar radiation effects on NO2 concentrations that vary with time and intra-urban location. The results also show that residential, commercial, and industrial land uses, and wind speed, temperature, and humidity, all impact NO2 concentrations. The R2 vary between 0.95 and 0.98.

Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0

NASA Astrophysics Data System (ADS)

Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.; Luke, Catherine M.

2016-08-01

Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model-data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. The new improved parameters for JULES are presented along with the associated uncertainties for each parameter.

Algorithm for Autonomous Landing

NASA Technical Reports Server (NTRS)

Kuwata, Yoshiaki

2011-01-01

Because of their small size, high maneuverability, and easy deployment, micro aerial vehicles (MAVs) are used for a wide variety of both civilian and military missions. One of their current drawbacks is the vast array of sensors (such as GPS, altimeter, radar, and the like) required to make a landing. Due to the MAV s small payload size, this is a major concern. Replacing the imaging sensors with a single monocular camera is sufficient to land a MAV. By applying optical flow algorithms to images obtained from the camera, time-to-collision can be measured. This is a measurement of position and velocity (but not of absolute distance), and can avoid obstacles as well as facilitate a landing on a flat surface given a set of initial conditions. The key to this approach is to calculate time-to-collision based on some image on the ground. By holding the angular velocity constant, horizontal speed decreases linearly with the height, resulting in a smooth landing. Mathematical proofs show that even with actuator saturation or modeling/ measurement uncertainties, MAVs can land safely. Landings of this nature may have a higher velocity than is desirable, but this can be compensated for by a cushioning or dampening system, or by using a system of legs to grab onto a surface. Such a monocular camera system can increase vehicle payload size (or correspondingly reduce vehicle size), increase speed of descent, and guarantee a safe landing by directly correlating speed to height from the ground.

Impacts of spectral nudging on the simulated surface air temperature in summer compared with the selection of shortwave radiation and land surface model physics parameterization in a high-resolution regional atmospheric model

NASA Astrophysics Data System (ADS)

Park, Jun; Hwang, Seung-On

2017-11-01

The impact of a spectral nudging technique for the dynamical downscaling of the summer surface air temperature in a high-resolution regional atmospheric model is assessed. The performance of this technique is measured by comparing 16 analysis-driven simulation sets of physical parameterization combinations of two shortwave radiation and four land surface model schemes of the model, which are known to be crucial for the simulation of the surface air temperature. It is found that the application of spectral nudging to the outermost domain has a greater impact on the regional climate than any combination of shortwave radiation and land surface model physics schemes. The optimal choice of two model physics parameterizations is helpful for obtaining more realistic spatiotemporal distributions of land surface variables such as the surface air temperature, precipitation, and surface fluxes. However, employing spectral nudging adds more value to the results; the improvement is greater than using sophisticated shortwave radiation and land surface model physical parameterizations. This result indicates that spectral nudging applied to the outermost domain provides a more accurate lateral boundary condition to the innermost domain when forced by analysis data by securing the consistency with large-scale forcing over a regional domain. This consequently indirectly helps two physical parameterizations to produce small-scale features closer to the observed values, leading to a better representation of the surface air temperature in a high-resolution downscaled climate.

Combining abiotic and biotic models - Hydraulical modeling to fill the gap between catchment and hydro-dynamic models

NASA Astrophysics Data System (ADS)

Guse, B.; Sulc, D.; Schmalz, B.; Fohrer, N.

2012-04-01

The European Water Framework Directive (WFD) requires a catchment-based approach, which is assessed in the IMPACT project by combining abiotic and biotic models. The core point of IMPACT is a model chain (catchment model -> 1-D-hydraulic model -> 3-D-hydro-morphodynamic model -> biotic habitat model) with the aim to estimate the occurrence of the target species of the WFD. Firstly, the model chain is developed for the current land use and climate conditions. Secondly, land use and climate change scenarios are developed at the catchment scale. The outputs of the catchment model for the scenarios are used as input for the next models within the model chain to estimate the effect of these changes on the target species. The eco-hydrological catchment model SWAT is applied for the Treene catchment in Northern Germany and delivers discharge and water quality parameters as a spatial explicit output for each subbasin. There is no water level information given by SWAT. However, water level values are needed as lower boundary condition for the hydro-dynamic and habitat models which are applied for the 300 m candidate reference reach. In order to fill the gap between the catchment and the hydro-morphodynamic model, the 1-D hydraulic model HEC-RAS is applied for a 3 km long reach transect from the next upstream hydrological station until the upper bound of the candidate study reach. The channel geometry for HEC-RAS was estimated based on 96 cross-sections which were measured in the IMPACT project. By using available discharge and water level measurements from the hydrological station and own flow velocity measurements, the channel resistence was estimated. HEC-RAS was run with different statistical indices (mean annual drought, mean discharge, …) for steady flow conditions. The rating curve was then constructed for the target cross-section, i.e. the lower bound of the candidate study reach, to fulfill the combining with the hydro- and morphodynamic models. These statistical indices can also be calculated for the discharge series provided by land use and climate scenarios. In this way, the effect of land use and climate change on the catchment and the hydraulic processes can be assessed.

Modeling Environmental Controls on Tree Water Use at Different Temporal scales

NASA Astrophysics Data System (ADS)

Guan, H.; Wang, H.; Simmons, C. T.

2014-12-01

Vegetation covers 70% of land surface, significantly influencing water and carbon exchange between land surface and the atmosphere. Vegetation transpiration (Et) contributes 80% of the global terrestrial evapotranspiration, making an adequate illustration of how important vegetation is to any hydrological or climatological applications. Transpiration can be estimated through upscaling from sap flow measurements on selected trees. Alternatively, transpiration (or tree water use for forests) can be correlated with environmental variables or estimated in land surface simulations in which a canopy conductance (gc) model is often used. Transpiration and canopy conductance are constrained by supply and demand control factors. Some previous studies estimated Et and gc considering the stresses from both the supply (soil water condition) and demand (e.g. temperature, vapor pressure deficit, solar radiation) factors, while some only considered the demand controls. In this study, we examined the performance of two types of models at daily and half-hourly scales for transpiration and canopy conductance modelling based on a native species in South Australia. The results show that the significance of soil water condition for Et and gc modelling varies with time scales. The model parameter values also vary across time scales. This result calls for attention in choosing models and parameter values for soil-plant-atmosphere continuum and land surface modeling.

Comparison of tropospheric ozone profiles measured by lidars simultaneously over land and water during the 2017 NASA OWLETS campaign

NASA Astrophysics Data System (ADS)

Gronoff, G.; Sullivan, J.; Berkoff, T.; Carrion, W.; Farris, B.

2017-12-01

The NASA Langley Mobile Ozone Lidar (LMOL) and NASA Goddard's lidar (TROPOZ) have routinely measured tropospheric ozone profiles in support of various NASA campaigns and local field studies since 2013 (e.g. DISCOVER-AQ 2014). They are both charter members of the NASA Tropospheric Lidar Network (TOLNet) and were constructed within transportable containers, allowing for observations directly within a variety of complex environments. To gain a better understanding of ozone's interactions close to the surface, both of these instruments have recently designed and optimized near field optical elements for ozone detection. One of the major difficulties for the modeling and satellite communities are the sharp transition regions, both horizontal and vertical, such as the land-water gradients in O3 near coastal/urban regions that are driven by differences in surface deposition, boundary layer height, and cloud coverage.To better understand these gradients, both lidars were deployed in the Hampton Roads / Tidewater region, in Virginia, in July-August 2017, in the context of the OWLETS (Ozone Water Land Environment Transition Study) campaign. The TROPOZ lidar was deployed above land at NASA LaRC, while the LMOL lidar was deployed on the Chesapeake Bay Bridge Tunnel third island, being de-facto an over-water lidar. The distance between the two lidars was approximately 30 km. Strong differences between the two lidars measurements were observed. Some influence of the ship traffic can be seen over water, but does not affect the observations above 300m. Overall, some important discrepancies between the modeling and the lidar observations over water were found. These results shows the importance of making more measurements over water to better constrain pollution models.

Determination of land use in Minnesota by automatic interpretation of ERTS MSS data

NASA Technical Reports Server (NTRS)

Zirkle, R. E.; Pile, D. R.

1973-01-01

This program aims to determine the feasibility of identifying land use in Minnesota by automatic interpretation of ERTS-MSS data. Ultimate objectives include establishment of land use delineation and quantification by computer processing with a minimum of human operator interaction. This implies not only that reflectivity as a function of calendar time can be catalogued effectively, but also that the effects of uncontrolled variables can be identified and compensated. Clouds are the major uncontrollable data pollutant, so part of the initial effort is devoted to determining their effect and the construction of a model to help correct or justifiably ignore affected data. Other short range objectives are to identify and verify measurements giving results of importance to land managers. Lake-counting is a prominent example. Open water is easily detected in band 7 data with some support from either band 4 or band 5 to remove ambiguities. Land managers and conservationists commission studies periodically to measure water bodies and total water count within specified areas.

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

USGS Publications Warehouse

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

2010-01-01

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

Evaluation of Ten Methods for Initializing a Land Surface Model

NASA Technical Reports Server (NTRS)

Rodell, M.; Houser, P. R.; Berg, A. A.; Famiglietti, J. S.

2005-01-01

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth"s water cycle and climate variability. NASA"s Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type).

Landscape pattern and car use: Linking household data with satellite imagery

NASA Astrophysics Data System (ADS)

Keller, R.; Vance, C.

2013-12-01

Landscape pattern has long been hypothesized to influence automobile dependency. Because choices about land development tend to have long-lasting impacts that span over decades, understanding the magnitude of this influence is critical to the design of policies to reduce emissions and other negative externalities associated with car use. Combining household survey data from Germany with satellite imagery and other geo-referenced data sources, we undertake an econometric analysis of the relation between landscape pattern and automobile dependency. Specifically, we employ a two-part model to investigate two dimensions of car use, the discrete decision to own a car and, conditional upon ownership, the continuous decision of how far to drive. Results indicate that landscape pattern, as captured by measures of both land cover (e.g. the extent of open space and landscape diversity) and land use (e.g. the density of regional businesses) are important predictors of car ownership and use. Other policy-relevant variables, such as fuel prices and public transit infrastructure, are also identified as correlates. Based on the magnitude of our estimates, we conclude that carefully considered land development and zoning measures - ones that encourage dense development, diverse land cover and mixed land use - can have beneficial impacts in reducing car dependency that extend far into the future. Key terms: Landscape pattern, Satellite imagery, Germany, Two-part model Figure 1. Distribution of Elasticities of Landscape and Social Effects on German Household Weekly Car Use Results from Two Part Model N = 13,089 (probit) N = 10,987 (OLS)Robust standard errors in parentheses***, **, and *, denotes significance at the 0.01, 0.05, and 0.1 levels

a New Survey on Self-Tuning Integrated Low-Cost Gps/ins Vehicle Navigation System in Harsh Environment

NASA Astrophysics Data System (ADS)

Navidi, N.; Landry, R., Jr.

2015-08-01

Nowadays, Global Positioning System (GPS) receivers are aided by some complementary radio navigation systems and Inertial Navigation Systems (INS) to obtain more accuracy and robustness in land vehicular navigation. Extended Kalman Filter (EKF) is an acceptable conventional method to estimate the position, the velocity, and the attitude of the navigation system when INS measurements are fused with GPS data. However, the usage of the low-cost Inertial Measurement Units (IMUs) based on the Micro-Electro-Mechanical Systems (MEMS), for the land navigation systems, reduces the precision and stability of the navigation system due to their inherent errors. The main goal of this paper is to provide a new model for fusing low-cost IMU and GPS measurements. The proposed model is based on EKF aided by Fuzzy Inference Systems (FIS) as a promising method to solve the mentioned problems. This model considers the parameters of the measurement noise to adjust the measurement and noise process covariance. The simulation results show the efficiency of the proposed method to reduce the navigation system errors compared with EKF.

Understanding the effect of watershed characteristic on the runoff using SCS curve number

NASA Astrophysics Data System (ADS)

Damayanti, Frieta; Schneider, Karl

2015-04-01

Runoff modeling is a key component in watershed management. The temporal course and amount of runoff is a complex function of a multitude of parameters such as climate, soil, topography, land use, and water management. Against the background of the current rapid environmental change, which is due to both i) man-made changes (e.g. urban development, land use change, water management) as well as ii) changes in the natural systems (e.g. climate change), understanding and predicting the impacts of these changes upon the runoff is very important and affects the wellbeing of many people living in the watershed. A main tool for predictions is hydrologic models. Particularly process based models are the method of choice to assess the impact of land use and climate change. However, many regions which experience large changes in the watersheds can be described as rather data poor, which limits the applicability of such models. This is particularly also true for the Telomoyo Watershed (545 km2) which is located in southern part of Central Java province. The average annual rainfall of the study area reaches 2971 mm. Irrigated paddy field are the dominating land use (35%), followed by built-up area and dry land agriculture. The only available soil map is the FAO soil digital map of the world, which provides rather general soil information. A field survey accompanied by a lab analysis 65 soil samples of was carried out to provide more detailed soil texture information. The soil texture map is a key input in the SCS method to define hydrological soil groups. In the frame of our study on 'Integrated Analysis on Flood Risk of Telomoyo Watershed in Response to the Climate and Land Use Change' funded by the German Academic Exchange service (DAAD) we analyzed the sensitivity of the modeled runoff upon the choice of the method to estimate the CN values using the SCS-CN method. The goal of this study is to analyze the impact of different data sources on the curve numbers and the estimated runoff. CN values were estimated using the field measurements of soil textures for different combinations of land use and topography. To transfer the local soil texture measurements to the watershed domain a statistical analysis using the frequency distribution of the measured soil textures is applied and used to derive the effective CN value for a given land use, topography and soil texture combination. Since the curve numbers change as a function of parameter combinations, the effect of different methods to estimate the curve number upon the runoff is analyzed and compared to the straight forward method of using the data from the FAO soil map.

Landing pressure loads of the 140A/B space shuttle orbiter (model 43-0) determined in the Rockwell International low speed wind tunnel (OA69), volume 1. [wind tunnel tests

NASA Technical Reports Server (NTRS)

Soard, T. L.

1975-01-01

Wind tunnel tests of a 0.0405 scale model of the -1404A/B configuration of the Space Shuttle Vehicle Orbiter are presented. Pressure loads data were obtained from the orbiter in the landing configuration in the presence of the ground for structural strength analysis. This was accomplished by locating as many as 30 static pressure bugs at various locations on external model surfaces as each configuration was tested. A complete pressure loads survey was generated for each configuration by combining data from all bug locations, and these loads are described for the fuselage, wing, vertical tail, and landing gear doors. Aerodynamic force data was measured by a six component internal strain gage balance. This data was recorded to correct model angles of attack and sideslip for sting and balance deflections and to determine the aerodynamic effects of landing gear extension. All testing was conducted at a Mach number of 0.165 and a Reynolds number of 1.2 million per foot. Photographs of test configurations are shown.

Crows Landing noise measurement study : summary of measurements, data and analysis for the MD600N helicopter

DOT National Transportation Integrated Search

2004-05-31

The U.S. Department of Transportation, John A. Volpe National Transportation Systems Center (Volpe Center), Environmental Measurement and Modeling Division, provided technical support to the Federal Aviation Administration, as a part of a National Ro...

Catchment Legacies and Time Lags: A Parsimonious Watershed Model to Predict the Effects of Legacy Storage on Nitrogen Export

PubMed Central

Van Meter, Kimberly J.; Basu, Nandita B.

2015-01-01

Nutrient legacies in anthropogenic landscapes, accumulated over decades of fertilizer application, lead to time lags between implementation of conservation measures and improvements in water quality. Quantification of such time lags has remained difficult, however, due to an incomplete understanding of controls on nutrient depletion trajectories after changes in land-use or management practices. In this study, we have developed a parsimonious watershed model for quantifying catchment-scale time lags based on both soil nutrient accumulations (biogeochemical legacy) and groundwater travel time distributions (hydrologic legacy). The model accurately predicted the time lags observed in an Iowa watershed that had undergone a 41% conversion of area from row crop to native prairie. We explored the time scales of change for stream nutrient concentrations as a function of both natural and anthropogenic controls, from topography to spatial patterns of land-use change. Our results demonstrate that the existence of biogeochemical nutrient legacies increases time lags beyond those due to hydrologic legacy alone. In addition, we show that the maximum concentration reduction benefits vary according to the spatial pattern of intervention, with preferential conversion of land parcels having the shortest catchment-scale travel times providing proportionally greater concentration reductions as well as faster response times. In contrast, a random pattern of conversion results in a 1:1 relationship between percent land conversion and percent concentration reduction, irrespective of denitrification rates within the landscape. Our modeling framework allows for the quantification of tradeoffs between costs associated with implementation of conservation measures and the time needed to see the desired concentration reductions, making it of great value to decision makers regarding optimal implementation of watershed conservation measures. PMID:25985290

Catchment legacies and time lags: a parsimonious watershed model to predict the effects of legacy storage on nitrogen export.

PubMed

Van Meter, Kimberly J; Basu, Nandita B

2015-01-01

Nutrient legacies in anthropogenic landscapes, accumulated over decades of fertilizer application, lead to time lags between implementation of conservation measures and improvements in water quality. Quantification of such time lags has remained difficult, however, due to an incomplete understanding of controls on nutrient depletion trajectories after changes in land-use or management practices. In this study, we have developed a parsimonious watershed model for quantifying catchment-scale time lags based on both soil nutrient accumulations (biogeochemical legacy) and groundwater travel time distributions (hydrologic legacy). The model accurately predicted the time lags observed in an Iowa watershed that had undergone a 41% conversion of area from row crop to native prairie. We explored the time scales of change for stream nutrient concentrations as a function of both natural and anthropogenic controls, from topography to spatial patterns of land-use change. Our results demonstrate that the existence of biogeochemical nutrient legacies increases time lags beyond those due to hydrologic legacy alone. In addition, we show that the maximum concentration reduction benefits vary according to the spatial pattern of intervention, with preferential conversion of land parcels having the shortest catchment-scale travel times providing proportionally greater concentration reductions as well as faster response times. In contrast, a random pattern of conversion results in a 1:1 relationship between percent land conversion and percent concentration reduction, irrespective of denitrification rates within the landscape. Our modeling framework allows for the quantification of tradeoffs between costs associated with implementation of conservation measures and the time needed to see the desired concentration reductions, making it of great value to decision makers regarding optimal implementation of watershed conservation measures.

Earth System Modeling Tested for CLM4.5 in a Costa Rican Tropical Montane Rainforest

NASA Astrophysics Data System (ADS)

Song, J.; Miller, G. R.; Cahill, A. T.; Aparecido, L. M. T.; Moore, G. W.

2017-12-01

Terrestrial ecosystems in the tropics are important for global carbon and water cycling, which makes modeling of their land-surface processes essential for accurate understanding of land-atmosphere interactions. However, modeling of tropical regions, especially mountainous ones, is known to be subject to significant errors in the prediction of evapotranspiration. Our previous work has highlighted the effects of the prolonged wetness experienced by such sites, focusing on carbon and water exchange at the leaf/stand level. Here, we explore the implications these findings have for modeling at the stand/canopy scale. This study examined the performance of the Community Land Model (CLM4.5) against measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4,000 mm of mean annual precipitation. Measurements include leaf temperatures, transpiration (sap flows), fluxes via eddy-covariance, and vertical profiles of H2O and CO2 concentrations, micrometeorological variables, and leaf wetness. In this work, results from point-scale CLM4.5 were compared to canopy data. The model fails to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). We found that soil and leaf temperatures were overestimated (≈ +2°C) at noon and underestimated (≈ -1°C) during the night; daily transpiration was approximately double than that observed. Simulated leaf wetness deviated significantly from the measurements, both in timing and extent, which affected temperatures and evapotranspiration partitioning. Slope effects appeared in the average diurnal variations of surface albedo and carbon flux from actual data but were not captured in CLM. Our investigation indicated that interception and aerodynamic resistance models contribute to model errors, suggesting potential improvements for modeling in very wet and/or mountainous regions.

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.

Grand challenges in understanding the interplay of climate and land changes

DOE PAGES

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.; ...

2017-03-28

Half of the Earth s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affects a myriad of land surface processes and our adaptation behaviors. We here review the status and major knowledge gaps of studying the interactions of land and atmospheric changes and present eleven grand challenge areas for scientific research and adaptation communities in the coming decade: (1) collective and separate impacts of major land changes and the interactions with non-land-change factors such as atmospheric CO2 increase, (2) carbon and other biogeochemicalmore » cycles, (3) climatically relevant biospheric emissions such as aerosols, (4) water cycle, (5) agriculture, (6) urbanization, (7) gradual acclimation of plants, communities, and ecosystems to climate and environmental changes, (8) plant migration, (9) land use projections, (10) reduction of uncertainties in models and data, and finally (11) adaptation strategies. We conclude that we need to create and maintain a close cross-disciplinary coordination between measurements and process representation in models to analyze complex multi-facet interrelated perturbations and feedbacks between land and climate changes. Along with major scientific research thrusts, land-use and land cover change mitigation and adaptation assessments should be strengthened to identify barriers that need to be overcome, evaluate and prioritize opportunities, and examine how decision making processes work in specific contexts.« less

Grand challenges in understanding the interplay of climate and land changes

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

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.

Half of the Earth s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affects a myriad of land surface processes and our adaptation behaviors. We here review the status and major knowledge gaps of studying the interactions of land and atmospheric changes and present eleven grand challenge areas for scientific research and adaptation communities in the coming decade: (1) collective and separate impacts of major land changes and the interactions with non-land-change factors such as atmospheric CO2 increase, (2) carbon and other biogeochemicalmore » cycles, (3) climatically relevant biospheric emissions such as aerosols, (4) water cycle, (5) agriculture, (6) urbanization, (7) gradual acclimation of plants, communities, and ecosystems to climate and environmental changes, (8) plant migration, (9) land use projections, (10) reduction of uncertainties in models and data, and finally (11) adaptation strategies. We conclude that we need to create and maintain a close cross-disciplinary coordination between measurements and process representation in models to analyze complex multi-facet interrelated perturbations and feedbacks between land and climate changes. Along with major scientific research thrusts, land-use and land cover change mitigation and adaptation assessments should be strengthened to identify barriers that need to be overcome, evaluate and prioritize opportunities, and examine how decision making processes work in specific contexts.« less

Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use

USGS Publications Warehouse

Breuer, L.; Huisman, J.A.; Willems, P.; Bormann, H.; Bronstert, A.; Croke, B.F.W.; Frede, H.-G.; Graff, T.; Hubrechts, L.; Jakeman, A.J.; Kite, G.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Viney, N.R.

2009-01-01

This paper introduces the project on 'Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM)' that aims at investigating the envelope of predictions on changes in hydrological fluxes due to land use change. As part of a series of four papers, this paper outlines the motivation and setup of LUCHEM, and presents a model intercomparison for the present-day simulation results. Such an intercomparison provides a valuable basis to investigate the effects of different model structures on model predictions and paves the ground for the analysis of the performance of multi-model ensembles and the reliability of the scenario predictions in companion papers. In this study, we applied a set of 10 lumped, semi-lumped and fully distributed hydrological models that have been previously used in land use change studies to the low mountainous Dill catchment, Germany. Substantial differences in model performance were observed with Nash-Sutcliffe efficiencies ranging from 0.53 to 0.92. Differences in model performance were attributed to (1) model input data, (2) model calibration and (3) the physical basis of the models. The models were applied with two sets of input data: an original and a homogenized data set. This homogenization of precipitation, temperature and leaf area index was performed to reduce the variation between the models. Homogenization improved the comparability of model simulations and resulted in a reduced average bias, although some variation in model data input remained. The effect of the physical differences between models on the long-term water balance was mainly attributed to differences in how models represent evapotranspiration. Semi-lumped and lumped conceptual models slightly outperformed the fully distributed and physically based models. This was attributed to the automatic model calibration typically used for this type of models. Overall, however, we conclude that there was no superior model if several measures of model performance are considered and that all models are suitable to participate in further multi-model ensemble set-ups and land use change scenario investigations. ?? 2008 Elsevier Ltd. All rights reserved.

Estimating surface fluxes over middle and upper streams of the Heihe River Basin with ASTER imagery

NASA Astrophysics Data System (ADS)

Ma, W.; Ma, Y.; Hu, Z.; Su, Z.; Wang, J.; Ishikawa, H.

2011-05-01

Land surface heat fluxes are essential measures of the strengths of land-atmosphere interactions involving energy, heat and water. Correct parameterization of these fluxes in climate models is critical. Despite their importance, state-of-the-art observation techniques cannot provide representative areal averages of these fluxes comparable to the model grid. Alternative methods of estimation are thus required. These alternative approaches use (satellite) observables of the land surface conditions. In this study, the Surface Energy Balance System (SEBS) algorithm was evaluated in a cold and arid environment, using land surface parameters derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Field observations and estimates from SEBS were compared in terms of net radiation flux (Rn), soil heat flux (G0), sensible heat flux (H) and latent heat flux (λE) over a heterogeneous land surface. As a case study, this methodology was applied to the experimental area of the Watershed Allied Telemetry Experimental Research (WATER) project, located on the mid-to-upstream sections of the Heihe River in northwest China. ASTER data acquired between 3 May and 4 June 2008, under clear-sky conditions were used to determine the surface fluxes. Ground-based measurements of land surface heat fluxes were compared with values derived from the ASTER data. The results show that the derived surface variables and the land surface heat fluxes furnished by SEBS in different months over the study area are in good agreement with the observed land surface status under the limited cases (some cases looks poor results). So SEBS can be used to estimate turbulent heat fluxes with acceptable accuracy in areas where there is partial vegetation cover in exceptive conditions. It is very important to perform calculations using ground-based observational data for parameterization in SEBS in the future. Nevertheless, the remote-sensing results can provide improved explanations of land surface fluxes over varying land coverage at greater spatial scales.

Calibration of a Land Subsidence Model Using InSAR Data via the Ensemble Kalman Filter.

PubMed

Li, Liangping; Zhang, Meijing; Katzenstein, Kurt

2017-11-01

The application of interferometric synthetic aperture radar (InSAR) has been increasingly used to improve capabilities to model land subsidence in hydrogeologic studies. A number of investigations over the last decade show how spatially detailed time-lapse images of ground displacements could be utilized to advance our understanding for better predictions. In this work, we use simulated land subsidences as observed measurements, mimicking InSAR data to inversely infer inelastic specific storage in a stochastic framework. The inelastic specific storage is assumed as a random variable and modeled using a geostatistical method such that the detailed variations in space could be represented and also that the uncertainties of both characterization of specific storage and prediction of land subsidence can be assessed. The ensemble Kalman filter (EnKF), a real-time data assimilation algorithm, is used to inversely calibrate a land subsidence model by matching simulated subsidences with InSAR data. The performance of the EnKF is demonstrated in a synthetic example in which simulated surface deformations using a reference field are assumed as InSAR data for inverse modeling. The results indicate: (1) the EnKF can be used successfully to calibrate a land subsidence model with InSAR data; the estimation of inelastic specific storage is improved, and uncertainty of prediction is reduced, when all the data are accounted for; and (2) if the same ensemble is used to estimate Kalman gain, the analysis errors could cause filter divergence; thus, it is essential to include localization in the EnKF for InSAR data assimilation. © 2017, National Ground Water Association.

Pairing Coral Geochemical Analyses with an Ecosystem Services Model to Assess Drivers and Impacts of Sediment Delivery within Micronesia's Largest Estuary, Ngeremeduu Bay

NASA Astrophysics Data System (ADS)

Lewis, S.; Dunbar, R. B.; Mucciarone, D.; Barkdull, M.

2017-12-01

Scientific tools assessing impacts to watershed and coastal ecosystem services, like those from land-use land conversion (LULC), are critical for sustainable land management strategies. Small island nations are particularly vulnerable to LULC threats, especially sediment delivery, given their small spatial size and reliance on natural resources. In the Republic of Palau, a small Pacific island country, three major land-use activities—construction, fires, and agriculture— have increased sediment delivery to important estuarine and coastal habitats (i.e., rivers, mangroves, coral reefs) over the past 30 years. This project examines the predictive capacity of an ecosystem services model, Natural Capital Project's InVEST, for sediment delivery using historic land-use and coral geochemical analysis. These refined model projections are used to assess ecosystem services tradeoffs under different future land development and management scenarios. Coral cores (20-41cm in length) were sampled along a high-to-low sedimentation gradient (i.e., near major rivers (high-impact) and ocean (low-impact)) in Micronesia's largest estuary, Ngeremeduu Bay. Isotopic indicators of seasonality (δ18O and δ13C values (% VPDB)) were used to construct the age model for each core. Barium, Manganese, and Yttrium were used as trace metal proxies for sedimentation and measured in each core using a laser ablation ICP-MS. Finally, the Natural Capital Project's InVEST sediment delivery model was paired with Geospatial data to examine the drivers of sediment delivery (i.e., construction, farms and fires) within these two watersheds. A thirty-year record of trace metal to calcium ratios in coral skeletons show a peak in sedimentation during 2006 and 2007, and in 2012. These results suggest historic peaks in sediment delivery correlating to large-scale road construction and support previous findings that Ngeremeduu Bay has reached a tipping point of retaining sediment. Natural Capital's project InVEST sediment delivery model results suggest fires increases sediment exportation by an order of magnitude compared with the other major land-use activities. A refined measure of LULC from a novel database (earth-moving permits) will be used to develop a more accurate depiction of sediment delivery to estuarine and coastal habitats.

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

Estimating daily surface NO2 concentrations from satellite data - a case study over Hong Kong using land use regression models

NASA Astrophysics Data System (ADS)

Anand, Jasdeep S.; Monks, Paul S.

2017-07-01

Land use regression (LUR) models have been used in epidemiology to determine the fine-scale spatial variation in air pollutants such as nitrogen dioxide (NO2) in cities and larger regions. However, they are often limited in their temporal resolution, which may potentially be rectified by employing the synoptic coverage provided by satellite measurements. In this work a mixed-effects LUR model is developed to model daily surface NO2 concentrations over the Hong Kong SAR during the period 2005-2015. In situ measurements from the Hong Kong Air Quality Monitoring Network, along with tropospheric vertical column density (VCD) data from the OMI, GOME-2A, and SCIAMACHY satellite instruments were combined with fine-scale land use parameters to provide the spatiotemporal information necessary to predict daily surface concentrations. Cross-validation with the in situ data shows that the mixed-effects LUR model using OMI data has a high predictive power (adj. R2 = 0. 84), especially when compared with surface concentrations derived using the MACC-II reanalysis model dataset (adj. R2 = 0. 11). Time series analysis shows no statistically significant trend in NO2 concentrations during 2005-2015, despite a reported decline in NOx emissions. This study demonstrates the utility in combining satellite data with LUR models to derive daily maps of ambient surface NO2 for use in exposure studies.

Estimating Antarctica land topography from GRACE gravity and ICESat altimetry data

NASA Astrophysics Data System (ADS)

Wu, I.; Chao, B. F.; Chen, Y.

2009-12-01

We propose a new method combining GRACE (Gravity Recovery and Climate Experiment) gravity and ICESat (Ice, Cloud, and land Elevation Satellite) altimetry data to estimate the land topography for Antarctica. Antarctica is the fifth-largest continent in the world and about 98% of Antarctica is covered by ice, where in-situ measurements are difficult. Some experimental airborne radar and ground-based radar data have revealed very limited land topography beneath heavy ice sheet. To estimate the land topography for the full coverage of Antarctica, we combine GRACE data that indicate the mass distribution, with data of ICESat laser altimetry that provide high-resolution mapping of ice topography. Our approach is actually based on some geological constraints: assuming uniform densities of the land and ice considering the Airy-type isostasy. In the beginning we construct an initial model for the ice thickness and land topography based on the BEDMAP ice thickness and ICESat data. Thereafter we forward compute the model’s gravity field and compare with the GRACE observed data. Our initial model undergoes the adjustments to improve the fit between modeled results and the observed data. Final examination is done by comparing our results with previous but sparse observations of ice thickness to reconfirm the reliability of our results. As the gravitational inversion problem is non-unique, our estimating result is just one of all possibilities constrained by available data in optimal way.

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

Simultaneous inversion of multiple land surface parameters from MODIS optical-thermal observations

NASA Astrophysics Data System (ADS)

Ma, Han; Liang, Shunlin; Xiao, Zhiqiang; Shi, Hanyu

2017-06-01

Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface variables usually focus on individual parameters separately even from the same satellite observations, resulting in inconsistent products. Moreover, no efforts have been made to generate global products from integrated observations from the optical to Thermal InfraRed (TIR) spectrum. Particularly, Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal, which contains both reflected and emitted radiation. In this paper, we propose a unified algorithm for simultaneously retrieving six land surface parameters - Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Emissivity (LSE), Land Surface Temperature (LST), and Upwelling Longwave radiation (LWUP) by exploiting MODIS visible-to-TIR observations. We incorporate a unified physical radiative transfer model into a data assimilation framework. The MODIS visible-to-TIR time series datasets include the daily surface reflectance product and MIR-to-TIR surface radiance, which are atmospherically corrected from the MODIS data using the Moderate Resolution Transmittance program (MODTRAN, ver. 5.0). LAI was first estimated using a data assimilation method that combines MODIS daily reflectance data and a LAI phenology model, and then the LAI was input to the unified radiative transfer model to simulate spectral surface reflectance and surface emissivity for calculating surface broadband albedo and emissivity, and FAPAR. LST was estimated from the MIR-TIR surface radiance data and the simulated emissivity, using an iterative optimization procedure. Lastly, LWUP was estimated using the LST and surface emissivity. The retrieved six parameters were extensively validated across six representative sites with different biome types, and compared with MODIS, GLASS, and GlobAlbedo land surface products. The results demonstrate that the unified inversion algorithm can retrieve temporally complete and physically consistent land surface parameters, and provides more accurate estimates of surface albedo, LST, and LWUP than existing products, with R2 values of 0.93 and 0.62, RMSE of 0.029 and 0.037, and BIAS values of 0.016 and 0.012 for the retrieved and MODIS albedo products, respectively, compared with field albedo measurements; R2 values of 0.95 and 0.93, RMSE of 2.7 and 4.2 K, and BIAS values of -0.6 and -2.7 K for the retrieved and MODIS LST products, respectively, compared with field LST measurements; and R2 values of 0.93 and 0.94, RMSE of 18.2 and 22.8 W/m2, and BIAS values of -2.7 and -14.6 W/m2 for the retrieved and MODIS LWUP products, respectively, compared with field LWUP measurements.

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.

Appraising the capability of a land biosphere model as a tool in modelling land surface interactions: results from its validation at selected European ecosystems

NASA Astrophysics Data System (ADS)

North, M. R.; Petropoulos, G. P.; Ireland, G.; McCalmont, J. P.

2015-02-01

In this present study the ability of the SimSphere Soil Vegetation Atmosphere Transfer (SVAT) model in estimating key parameters characterising land surface interactions was evaluated. Specifically, SimSphere's performance in predicting Net Radiation (Rnet), Latent Heat (LE), Sensible Heat (H) and Air Temperature (Tair) at 1.3 and 50 m was examined. Model simulations were validated by ground-based measurements of the corresponding parameters for a total of 70 days of the year 2011 from 7 CarboEurope network sites. These included a variety of biomes, environmental and climatic conditions in the models evaluation. Overall, model performance can largely be described as satisfactory for most of the experimental sites and evaluated parameters. For all model parameters compared, predicted H fluxes consistently obtained the highest agreement to the in-situ data in all ecosystems, with an average RMSD of 55.36 W m-2. LE fluxes and Rnet also agreed well with the in-situ data with RSMDs of 62.75 and 64.65 W m-2 respectively. A good agreement between modelled and measured LE and H fluxes was found, especially for smoothed daily flux trends. For both Tair 1.3 m and Tair 50 m a mean RMSD of 4.14 and 3.54 °C was reported respectively. This work presents the first all-inclusive evaluation of SimSphere, particularly so in a European setting. Results of this study contribute decisively towards obtaining a better understanding of the model's structure and its correspondence to the real world system. Findings also further establish the model's capability as a useful teaching and research tool in modelling Earth's land surface interactions. This is of considerable importance in the light of the rapidly expanding use of the model worldwide, including ongoing research by various Space Agencies examining its synergistic use with Earth Observation data towards the development of operational products at a global scale.

Airframe noise prediction evaluation

NASA Technical Reports Server (NTRS)

Yamamoto, Kingo J.; Donelson, Michael J.; Huang, Shumei C.; Joshi, Mahendra C.

1995-01-01

The objective of this study is to evaluate the accuracy and adequacy of current airframe noise prediction methods using available airframe noise measurements from tests of a narrow body transport (DC-9) and a wide body transport (DC-10) in addition to scale model test data. General features of the airframe noise from these aircraft and models are outlined. The results of the assessment of two airframe prediction methods, Fink's and Munson's methods, against flight test data of these aircraft and scale model wind tunnel test data are presented. These methods were extensively evaluated against measured data from several configurations including clean, slat deployed, landing gear-deployed, flap deployed, and landing configurations of both DC-9 and DC-10. They were also assessed against a limited number of configurations of scale models. The evaluation was conducted in terms of overall sound pressure level (OASPL), tone corrected perceived noise level (PNLT), and one-third-octave band sound pressure level (SPL).

Land Cover Land Use change and soil organic carbon under climate variability in the semi-arid West African Sahel (1960-2050)

NASA Astrophysics Data System (ADS)

Dieye, Amadou M.

Land Cover Land Use (LCLU) change affects land surface processes recognized to influence climate change at local, national and global levels. Soil organic carbon is a key component for the functioning of agro-ecosystems and has a direct effect on the physical, chemical and biological characteristics of the soil. The capacity to model and project LCLU change is of considerable interest for mitigation and adaptation measures in response to climate change. A combination of remote sensing analyses, qualitative social survey techniques, and biogeochemical modeling was used to study the relationships between climate change, LCLU change and soil organic carbon in the semi-arid rural zone of Senegal between 1960 and 2050. For this purpose, four research hypotheses were addressed. This research aims to contribute to an understanding of future land cover land use change in the semi-arid West African Sahel with respect to climate variability and human activities. Its findings may provide insights to enable policy makers at local to national levels to formulate environmentally and economically adapted policy decisions. This dissertation research has to date resulted in two published and one submitted paper.

A remote sensing data assimilation system for cold land processes hydrologic estimation

NASA Astrophysics Data System (ADS)

Andreadis, Konstantinos M.

2009-12-01

Accurate forecasting of snow properties is important for effective water resources management, especially in mountainous areas. Model-based approaches are limited by biases and uncertainties. Remote sensing offers an opportunity for observation of snow properties over larger areas. Traditional approaches to direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover. To address these complications, a data assimilation system is developed and evaluated in a three-part research. The data assimilation system requires the embedding of a microwave emissions model which uses modeled snowpack properties. In the first part of this study, such a model is evaluated using multi-scale TB measurements from the Cold Land Processes Experiment. The model's ability to reproduce snowpack microphysical properties is evaluated through comparison with snowpit measurements, while TB predictions are evaluated through comparison with in-situ, aircraft and satellite measurements. Point comparisons showed limitations in the model, while the spatial averaging and the effects of forest cover suppressed errors in comparisons with aircraft measurements. The layered character of snowpacks increases the complexity of algorithms intended to retrieve snow properties from the snowpack microwave return signal. Implementation of a retrieval strategy requires knowledge of stratigraphy, which practically can only be produced by models. In the second part of this study, we describe a multi-layer model designed for such applications. The model coupled with a radiative transfer scheme improved the estimation of TB, while potential impacts when assimilating radiances are explored. A system that merges SWE model predictions and observations of SCE and TB, is evaluated in the third part of this study over one winter season in the Upper Snake River basin. Two data assimilation techniques, the Ensemble Kalman filter and the Ensemble Multiscale Kalman filter are tested with the multilayer snow model forced by downscaled re-analysis meteorological observations. Both the EnKF and EnMKF showed modest improvements when compared with the open-loop simulation, relative to a baseline simulation which used in-situ meteorological data, while comparisons with in-situ SWE measurements showed an overall improvement.

Vegetated land cover near residence is associated with ...

EPA Pesticide Factsheets

Abstract Background: Greater exposure to urban green spaces has been linked to reduced risks of depression, cardiovascular disease, diabetes and premature death. Alleviation of chronic stress is a hypothesized pathway to improved health. Previous studies linked chronic stress with biomarker-based measures of physiological dysregulation known as allostatic load. This study aimed to assess the relationship between vegetated land cover near residences and allostatic load. Methods: This cross-sectional population-based study involved 204 adult residents of the Durham-Chapel Hill, North Carolina metropolitan area. Exposure was quantified using high-resolution metrics of trees and herbaceous vegetation within 500 m of each residence derived from the U.S. Environmental Protection Agency’s EnviroAtlas land cover dataset. Eighteen biomarkers of immune, neuroendocrine, and metabolic functions were measured in serum or saliva samples. Allostatic load was defined as a sum of biomarker values dichotomized at specific percentiles of sample distribution. Regression analysis was conducted using generalized additive models with two-dimensional spline smoothing function of geographic coordinates, weighted measures of vegetated land cover allowing decay of effects with distance, and geographic and demographic covariates. Results: An inter-quartile range increase in distance-weighted vegetated land cover was associated with 37% (46%; 27%) reduced allostatic load; significantly

Land use impact on water quality: valuing forest services in terms of the water supply sector.

PubMed

Fiquepron, Julien; Garcia, Serge; Stenger, Anne

2013-09-15

The aim of this paper is to quantify the impact of the forest on raw water quality within the framework of other land uses. On the basis of measurements of quality parameters that were identified as being the most problematic (i.e., pesticides and nitrates), we modeled how water quality is influenced by land uses. In order to assess the benefits provided by the forest in terms of improved water quality, we used variations of drinking water prices that were determined by the operating costs of water supply services (WSS). Given the variability of links between forests and water quality, we chose to cover all of France using data observed in each administrative department (France is divided into 95 départements), including a description of WSS and information on land uses. We designed a model that describes the impact of land uses on water quality, as well as the operation of WSS and prices. This bioeconomic model was estimated by the generalized method of moments (GMM) to account for endogeneity and heteroscedasticity issues. We showed that the forest has a positive effect on raw water quality compared to other land uses, with an indirect impact on water prices, making them lower for consumers. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analyses and simulation to spatial pattern of land utilization in Guangzhu City

NASA Astrophysics Data System (ADS)

Zhang, Xin-chang; Zhang, Wen-jiang; Ma, Kun

2006-10-01

Based on Landsat TM remote sensing images in 1990 and 2000, we analyses the temporal and spatial pattern Characters of land use in the 1990s in Guangzhou city. We also simulate the scenarios of land-use pattern in 2010 by integrating the Markov process into cellular automata model. The results show that the area of constructions was rapid increasing during the last ten years of the 20th century, at the same time the arable land, woodland and unused land areas were decreasing, the orchard and water areas were rarely changed; In the first ten years of 21st century, land use pattern keep the change trend in the 1990s, land of constructions continue rapid increasing; arable land and unused land areas continue rapid decreasing; woodland, orchard and water areas keep steadily. Research shows that the extent of urban area has increased exponentially in Guangzhou city, no evidences show that the arable land decreasing rate will slow down in the near future. So, it is necessary to enhance the control functions of land use planning and take actives measures to protect arable land.

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

NASA Technical Reports Server (NTRS)

1990-01-01

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

Grand challenges in understanding the interplay of climate and land changes

USGS Publications Warehouse

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.; Ford, James D.; Fox, Andrew; Gallo, Kevin; Hatfield, Jerry L.; Henebry, Geoffrey M.; Huntington, Thomas G.; Liu, Zhihua; Loveland, Thomas R.; Norby, Richard J.; Sohl, Terry L.; Steiner, Allison L.; Yuan, Wenping; Zhang, Zhao; Zhao, Shuqing

2017-01-01

Half of Earth’s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decision-making processes work in specific contexts.

Modeling Land Use Change In A Tropical Environment Using Similar Hydrologic Response Units

NASA Astrophysics Data System (ADS)

Guardiola-Claramonte, M.; Troch, P.

2006-12-01

Montane mainland South East Asia comprises areas of great biological and cultural diversity. Over the last decades the region has overcome an important conversion from traditional agriculture to cash crop agriculture driven by regional and global markets. Our study aims at understanding the hydrological implications of these land use changes at the catchment scale. In 2004, networks of hydro-meteorological stations observing water and energy fluxes were installed in two 70 km2 catchments in Northern Thailand (Chiang Mai Province) and Southern China (Yunnan Province). In addition, a detailed soil surveying campaign was done at the moment of instrument installation. Land use is monitored periodically using satellite data. The Thai catchment is switching from small agricultural fields to large extensions of cash crops. The Chinese catchment is replacing the traditional forest for rubber plantations. A first comparative study based on catchments' geomorphologic characteristics, field observations and rainfall-runoff response revealed the dominant hydrologic processes in the catchments. Land use information is then translated into three different Hydrologic Response Units (HRU): rice paddies, pervious and impervious surfaces. The pervious HRU include different land uses such as different stages of forest development, rubber plantations, and agricultural fields; the impervious ones are urban areas, roads and outcrops. For each HRU a water and energy balance model is developed incorporating field observed hydrologic processes, measured field parameters, and literature-based vegetation and soil parameters to better describe the root zone, surface and subsurface flow characteristics without the need of further calibration. The HRU water and energy balance models are applied to single hillslopes and their integrated hydrologic response are compared for different land covers. Finally, the response of individual hillslopes is routed through the channel network to represent each of the basins. Results from the model are compared to measured catchment-scale water and energy fluxes.

Hydrologic Remote Sensing and Land Surface Data Assimilation.

PubMed

Moradkhani, Hamid

2008-05-06

Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear updating rule and assumption of jointly normal distribution of errors in state variables and observation.

Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales.

PubMed

Pratt, Bethany; Chang, Heejun

2012-03-30

The relationship among land cover, topography, built structure and stream water quality in the Portland Metro region of Oregon and Clark County, Washington areas, USA, is analyzed using ordinary least squares (OLS) and geographically weighted (GWR) multiple regression models. Two scales of analysis, a sectional watershed and a buffer, offered a local and a global investigation of the sources of stream pollutants. Model accuracy, measured by R(2) values, fluctuated according to the scale, season, and regression method used. While most wet season water quality parameters are associated with urban land covers, most dry season water quality parameters are related topographic features such as elevation and slope. GWR models, which take into consideration local relations of spatial autocorrelation, had stronger results than OLS regression models. In the multiple regression models, sectioned watershed results were consistently better than the sectioned buffer results, except for dry season pH and stream temperature parameters. This suggests that while riparian land cover does have an effect on water quality, a wider contributing area needs to be included in order to account for distant sources of pollutants. Copyright © 2012 Elsevier B.V. All rights reserved.

Rock size-frequency distributions on Mars and implications for Mars Exploration Rover landing safety and operations

NASA Astrophysics Data System (ADS)

Golombek, M. P.; Haldemann, A. F. C.; Forsberg-Taylor, N. K.; DiMaggio, E. N.; Schroeder, R. D.; Jakosky, B. M.; Mellon, M. T.; Matijevic, J. R.

2003-10-01

The cumulative fractional area covered by rocks versus diameter measured at the Pathfinder site was predicted by a rock distribution model that follows simple exponential functions that approach the total measured rock abundance (19%), with a steep decrease in rocks with increasing diameter. The distribution of rocks >1.5 m diameter visible in rare boulder fields also follows this steep decrease with increasing diameter. The effective thermal inertia of rock populations calculated from a simple empirical model of the effective inertia of rocks versus diameter shows that most natural rock populations have cumulative effective thermal inertias of 1700-2100 J m-2 s-0.5 K-1 and are consistent with the model rock distributions applied to total rock abundance estimates. The Mars Exploration Rover (MER) airbags have been successfully tested against extreme rock distributions with a higher percentage of potentially hazardous triangular buried rocks than observed at the Pathfinder and Viking landing sites. The probability of the lander impacting a >1 m diameter rock in the first 2 bounces is <3% and <5% for the Meridiani and Gusev landing sites, respectively, and is <0.14% and <0.03% for rocks >1.5 m and >2 m diameter, respectively. Finally, the model rock size-frequency distributions indicate that rocks >0.1 m and >0.3 m in diameter, large enough to place contact sensor instruments against and abrade, respectively, should be plentiful within a single sol's drive at the Meridiani and Gusev landing sites.

Measurement of Seafloor Deformation in the Marine Sector of the Campi Flegrei Caldera (Italy)

NASA Astrophysics Data System (ADS)

Iannaccone, Giovanni; Guardato, Sergio; Donnarumma, Gian Paolo; De Martino, Prospero; Dolce, Mario; Macedonio, Giovanni; Chierici, Francesco; Beranzoli, Laura

2018-01-01

We present an assessment of vertical seafloor deformation in the shallow marine sector of the Campi Flegrei caldera (southern Italy) obtained from GPS and bottom pressure recorder (BPR) data, acquired over the period April 2016 to July 2017 in the Gulf of Pozzuoli by a new marine infrastructure, MEDUSA. This infrastructure consists of four fixed buoys with GPS receivers; each buoy is connected by cable to a seafloor multisensor module hosting a BPR. The measured maximum vertical uplift of the seafloor is about 4.2 ± 0.4 cm. The MEDUSA data were then compared to the expected vertical displacement in the marine sector according to a Mogi model point source computed using only GPS land measurements. The results show that a single point source model of deformation is able to explain both the GPS land and seafloor data. Moreover, we demonstrate that a network of permanent GPS buoys represents a powerful tool to measure the seafloor vertical deformation field in shallow water. The performance of this system is comparable to on-land high-precision GPS networks, marking a significant achievement and advance in seafloor geodesy and extending volcano monitoring capabilities to shallow offshore areas (up to 100 m depth). The GPS measurements of MEDUSA have also been used to confirm that the BPR data provide an independent measure of the seafloor vertical uplift in shallow water.

The Use of CASES-97 Observations to Assess and Parameterize the Impact of Land-Surface Heterogeneity on Area-Average Surface Heat Fluxes for Large-Scale Coupled Atmosphere-Hydrology Models

NASA Technical Reports Server (NTRS)

Chen, Fei; Yates, David; LeMone, Margaret

2001-01-01

To understand the effects of land-surface heterogeneity and the interactions between the land-surface and the planetary boundary layer at different scales, we develop a multiscale data set. This data set, based on the Cooperative Atmosphere-Surface Exchange Study (CASES97) observations, includes atmospheric, surface, and sub-surface observations obtained from a dense observation network covering a large region on the order of 100 km. We use this data set to drive three land-surface models (LSMs) to generate multi-scale (with three resolutions of 1, 5, and 10 kilometers) gridded surface heat flux maps for the CASES area. Upon validating these flux maps with measurements from surface station and aircraft, we utilize them to investigate several approaches for estimating the area-integrated surface heat flux for the CASES97 domain of 71x74 square kilometers, which is crucial for land surface model development/validation and area water and energy budget studies. This research is aimed at understanding the relative contribution of random turbulence versus organized mesoscale circulations to the area-integrated surface flux at the scale of 100 kilometers, and identifying the most important effective parameters for characterizing the subgrid-scale variability for large-scale atmosphere-hydrology models.

Predicting storm runoff from different land-use classes using a geographical information system-based distributed model

NASA Astrophysics Data System (ADS)

Liu, Y. B.; Gebremeskel, S.; de Smedt, F.; Hoffmann, L.; Pfister, L.

2006-02-01

A method is presented to evaluate the storm runoff contributions from different land-use class areas within a river basin using the geographical information system-based hydrological model WetSpa. The modelling is based on division of the catchment into a grid mesh. Each cell has a unique response function independent of the functioning of other cells. Summation of the flow responses from the cells with the same land-use type results in the storm runoff contribution from these areas. The model was applied on the Steinsel catchment in the Alzette river basin, Grand Duchy of Luxembourg, with 52 months of meteo-hydrological measurements. The simulation results show that the direct runoff from urban areas is dominant for a flood event compared with runoff from other land-use areas in this catchment, and this tends to increase for small floods and for the dry-season floods, whereas the interflow from forested, pasture and agricultural field areas contributes to recession flow. It is demonstrated that the relative contribution from urban areas decreases with flow coefficient, that cropland relative contribution is nearly constant, and that the relative contribution from grassland and woodland increases with flow coefficient with regard to their percentage of land-use class areas within the study catchment.

Evaluation of improved land use and canopy representation in ...

EPA Pesticide Factsheets

Biogenic volatile organic compounds (BVOC) participate in reactions that can lead to secondarily formed ozone and particulate matter (PM) impacting air quality and climate. BVOC emissions are important inputs to chemical transport models applied on local to global scales but considerable uncertainty remains in the representation of canopy parameterizations and emission algorithms from different vegetation species. The Biogenic Emission Inventory System (BEIS) has been used to support both scientific and regulatory model assessments for ozone and PM. Here we describe a new version of BEIS which includes updated input vegetation data and canopy model formulation for estimating leaf temperature and vegetation data on estimated BVOC. The Biogenic Emission Landuse Database (BELD) was revised to incorporate land use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) land product and 2006 National Land Cover Database (NLCD) land coverage. Vegetation species data are based on the US Forest Service (USFS) Forest Inventory and Analysis (FIA) version 5.1 for 2002–2013 and US Department of Agriculture (USDA) 2007 census of agriculture data. This update results in generally higher BVOC emissions throughout California compared with the previous version of BEIS. Baseline and updated BVOC emission estimates are used in Community Multiscale Air Quality (CMAQ) Model simulations with 4 km grid resolution and evaluated with measurements of isoprene and monoterp

Qualifying Spirit and Opportunity to Martian Landing Loads with Centrifuge Testing

NASA Technical Reports Server (NTRS)

Coleman, Michelle R.; Davis, Greg

2004-01-01

This viewgraph presentation reviews the drop test used to test the Mars lander. The objective of the test was to demonstrate the structural and functional integrity of the development test Model (DTM). Rover Basepetal when subjected to the landing event. The test module was instrumented with accelerometers to measure the kinematic response of the test article during impact.

ANALYSIS OF WATER AND ENERGY FLUXES USING SATELLITE, ENERGY BALANCE MODELING AND OBSERVATIONS (Invited)

NASA Astrophysics Data System (ADS)

Irmak, A.

2009-12-01

Surface energy fluxes, including net radiation (Rn), sensible heat (H), latent heat (LE), and soil heat flux (G) are critical in surface energy balance of any terrain or landscapes. Estimation or measurement of these energy fluxes is important for completing the water balance in terrestrial ecosystems, and therefore accurately predicting the effects of global climate and land use change. The objectives of this study were to (1) use METRICtm (Mapping Evapotranspiration at high Resolution using Internalized Calibration) model for estimating land surface energy fluxes in Nebraska (NE) by utilizing satellite remote sensing data, (2) identify model bias in energy balance components compared with measurements from Bowen Ratio Energy Balance System (BREBS) in a subsurface drip-irrigated maize field in South-central Nebraska, and (3) understand the partitioning of available energy into latent heat for corn and soybean cropping systems at large scale. A total of 15 Landsat images were processed to estimate instantaneous surface energy fluxes at Landsat overpasses with METRIC model. Results showed that the model predictions of the surface energy fluxes and daily evapotranspiration were correlated well with the BREBS measurements. There is a need, however, to test the performance of the model with in-situ observations in other locations with different dataset before utilizing it for crucial water regulatory and policy decisions. The METRICtm approach illustrated how an ‘off-the-shelf’ model can be applied operationally over a significant time period and how that model behaves. The findings makes considerable contribution to our understanding of estimating land surface energy fluxes using remote sensing approach and experimentally describes the operational characteristics of METRICtm and presents its limitations.

Influence of an urban canopy model and PBL schemes on vertical mixing for air quality modeling over Greater Paris

NASA Astrophysics Data System (ADS)

Kim, Youngseob; Sartelet, Karine; Raut, Jean-Christophe; Chazette, Patrick

2015-04-01

Impacts of meteorological modeling in the planetary boundary layer (PBL) and urban canopy model (UCM) on the vertical mixing of pollutants are studied. Concentrations of gaseous chemical species, including ozone (O3) and nitrogen dioxide (NO2), and particulate matter over Paris and the near suburbs are simulated using the 3-dimensional chemistry-transport model Polair3D of the Polyphemus platform. Simulated concentrations of O3, NO2 and PM10/PM2.5 (particulate matter of aerodynamic diameter lower than 10 μm/2.5 μm, respectively) are first evaluated using ground measurements. Higher surface concentrations are obtained for PM10, PM2.5 and NO2 with the MYNN PBL scheme than the YSU PBL scheme because of lower PBL heights in the MYNN scheme. Differences between simulations using different PBL schemes are lower than differences between simulations with and without the UCM and the Corine land-use over urban areas. Regarding the root mean square error, the simulations using the UCM and the Corine land-use tend to perform better than the simulations without it. At urban stations, the PM10 and PM2.5 concentrations are over-estimated and the over-estimation is reduced using the UCM and the Corine land-use. The ability of the model to reproduce vertical mixing is evaluated using NO2 measurement data at the upper air observation station of the Eiffel Tower, and measurement data at a ground station near the Eiffel Tower. Although NO2 is under-estimated in all simulations, vertical mixing is greatly improved when using the UCM and the Corine land-use. Comparisons of the modeled PM10 vertical distributions to distributions deduced from surface and mobile lidar measurements are performed. The use of the UCM and the Corine land-use is crucial to accurately model PM10 concentrations during nighttime in the center of Paris. In the nocturnal stable boundary layer, PM10 is relatively well modeled, although it is over-estimated on 24 May and under-estimated on 25 May. However, PM10 is under-estimated on both days in the residual layer, and over-estimated on both days over the residual layer. The under-estimations in the residual layer are partly due to difficulties to estimate the PBL height, to an over-estimation of vertical mixing during nighttime at high altitudes and to uncertainties in PM10 emissions. The PBL schemes and the UCM influence the PM vertical distributions not only because they influence vertical mixing (PBL height and eddy-diffusion coefficient), but also horizontal wind fields and humidity. However, for the UCM, it is the influence on vertical mixing that impacts the most the PM10 vertical distribution below 1.5 km.

Comparative approaches from empirical to mechanistic simulation modelling in Land Evaluation studies

NASA Astrophysics Data System (ADS)

Manna, P.; Basile, A.; Bonfante, A.; Terribile, F.

2009-04-01

The Land Evaluation (LE) comprise the evaluation procedures to asses the attitudes of the land to a generic or specific use (e.g. biomass production). From local to regional and national scale the approach to the land use planning should requires a deep knowledge of the processes that drive the functioning of the soil-plant-atmosphere system. According to the classical approaches the assessment of attitudes is the result of a qualitative comparison between the land/soil physical properties and the land use requirements. These approaches have a quick and inexpensive applicability; however, they are based on empirical and qualitative models with a basic knowledge structure specifically built for a specific landscape and for the specific object of the evaluation (e.g. crop). The outcome from this situation is the huge difficulties in the spatial extrapolation of the LE results and the rigidity of the system. Modern techniques instead, rely on the application of mechanistic and quantitative simulation modelling that allow a dynamic characterisation of the interrelated physical and chemical processes taking place in the soil landscape. Moreover, the insertion of physical based rules in the LE procedure may make it less difficult in terms of both extending spatially the results and changing the object (e.g. crop species, nitrate dynamics, etc.) of the evaluation. On the other side these modern approaches require high quality and quantity of input data that cause a significant increase in costs. In this scenario nowadays the LE expert is asked to choose the best LE methodology considering costs, complexity of the procedure and benefits in handling a specific land evaluation. In this work we performed a forage maize land suitability study by comparing 9 different methods having increasing complexity and costs. The study area, of about 2000 ha, is located in North Italy in the Lodi plain (Po valley). The range of the 9 employed methods ranged from standard LE approaches to the extensive use of simulation modelling (SWAP and CropSyst), using as data input pre-existing soil information (soil map 1:50000) and also hydraulic properties measured as well estimated by PTF. The comparison between the different methods was based on both cost and predictive ability of each of the methods. The latter was evaluated by comparison to the estimate of forage maize biomass obtained by using locally tested remote sensing measurements. Statistical indexes like correlation, relative variance and ANOVA test were applied. As expected, higher method complexity corresponds to higher quality/quantity of input parameters and as consequence higher costs. Generally, results show that more complex methods gave better results in terms of their predictive ability and those operating on measurements gave better performance than those operating on PTF. Moreover, the best predictive results were obtained abandoning the support of the soil mapping units, incrementing dramatically the number of sampling and analysis and applying the simulation modelling on real benchmark soils rather than averaging more soils observations. Keywords: Land Evaluation, simulation modelling, CropSyst, SWAP, NDVI.

Accounting for results: how conservation organizations report performance information.

PubMed

Rissman, Adena R; Smail, Robert

2015-04-01

Environmental program performance information is in high demand, but little research suggests why conservation organizations differ in reporting performance information. We compared performance measurement and reporting by four private-land conservation organizations: Partners for Fish and Wildlife in the US Fish and Wildlife Service (national government), Forest Stewardship Council-US (national nonprofit organization), Land and Water Conservation Departments (local government), and land trusts (local nonprofit organization). We asked: (1) How did the pattern of performance reporting relationships vary across organizations? (2) Was political conflict among organizations' principals associated with greater performance information? and (3) Did performance information provide evidence of program effectiveness? Based on our typology of performance information, we found that most organizations reported output measures such as land area or number of contracts, some reported outcome indicators such as adherence to performance standards, but few modeled or measured environmental effects. Local government Land and Water Conservation Departments reported the most types of performance information, while local land trusts reported the fewest. The case studies suggest that governance networks influence the pattern and type of performance reporting, that goal conflict among principles is associated with greater performance information, and that performance information provides unreliable causal evidence of program effectiveness. Challenging simple prescriptions to generate more data as evidence, this analysis suggests (1) complex institutional and political contexts for environmental program performance and (2) the need to supplement performance measures with in-depth evaluations that can provide causal inferences about program effectiveness.

Accounting for Results: How Conservation Organizations Report Performance Information

NASA Astrophysics Data System (ADS)

Rissman, Adena R.; Smail, Robert

2015-04-01

Environmental program performance information is in high demand, but little research suggests why conservation organizations differ in reporting performance information. We compared performance measurement and reporting by four private-land conservation organizations: Partners for Fish and Wildlife in the US Fish and Wildlife Service (national government), Forest Stewardship Council—US (national nonprofit organization), Land and Water Conservation Departments (local government), and land trusts (local nonprofit organization). We asked: (1) How did the pattern of performance reporting relationships vary across organizations? (2) Was political conflict among organizations' principals associated with greater performance information? and (3) Did performance information provide evidence of program effectiveness? Based on our typology of performance information, we found that most organizations reported output measures such as land area or number of contracts, some reported outcome indicators such as adherence to performance standards, but few modeled or measured environmental effects. Local government Land and Water Conservation Departments reported the most types of performance information, while local land trusts reported the fewest. The case studies suggest that governance networks influence the pattern and type of performance reporting, that goal conflict among principles is associated with greater performance information, and that performance information provides unreliable causal evidence of program effectiveness. Challenging simple prescriptions to generate more data as evidence, this analysis suggests (1) complex institutional and political contexts for environmental program performance and (2) the need to supplement performance measures with in-depth evaluations that can provide causal inferences about program effectiveness.

Use of terrestrial laser scanning (TLS) for monitoring and modelling of geomorphic processes and phenomena at a small and medium spatial scale in Polar environment (Scott River — Spitsbergen)

NASA Astrophysics Data System (ADS)

Kociuba, Waldemar; Kubisz, Waldemar; Zagórski, Piotr

2014-05-01

The application of Terrestrial Laser Scanning (TLS) for precise modelling of land relief and quantitative estimation of spatial and temporal transformations can contribute to better understanding of catchment-forming processes. Experimental field measurements utilising the 3D laser scanning technology were carried out within the Scott River catchment located in the NW part of the Wedel Jarlsberg Land (Spitsbergen). The measurements concerned the glacier-free part of the Scott River valley floor with a length of 3.5 km and width from 0.3 to 1.5 km and were conducted with a state-of-the-art medium-range stationary laser scanner, a Leica Scan Station C10. A complex set of measurements of the valley floor were carried out from 86 measurement sites interrelated by the application of 82 common 'target points'. During scanning, from 5 to 19 million measurements were performed at each of the sites, and a point-cloud constituting a 'model space' was obtained. By merging individual 'model spaces', a Digital Surface Model (DSM) of the Scott River valley was obtained, with a co-registration error not exceeding ± 9 mm. The accuracy of the model permitted precise measurements of dimensions of landforms of varied scales on the main valley floor and slopes and in selected sub-catchments. The analyses verified the efficiency of the measurement system in Polar meteorological conditions of Spitsbergen in mid-summer.

Modeling suspended sediment sources and transport in the Ishikari River Basin, Japan using SPARROW

NASA Astrophysics Data System (ADS)

Duan, W.; He, B.; Takara, K.; Luo, P.; Nover, D.; Hu, M.

2014-10-01

It is important to understand the mechanisms that control suspended sediment (SS) fate and transport in rivers as high suspended sediment loads have significant impacts on riverine hydroecology. In this study, the watershed model SPARROW (SPAtially Referenced Regression on Watershed Attributes) was applied to estimate the sources and transport of SS in surface waters of the Ishikari River Basin (14 330 km2), the largest watershed on Hokkaido Island, Japan. The final developed SPARROW model has four source variables (developing lands, forest lands, agricultural lands, and stream channels), three landscape delivery variables (slope, soil permeability, and precipitation), two in-stream loss coefficients including small stream (streams with drainage area < 200 km2), large stream, and reservoir attenuation. The model was calibrated using measurements of SS from 31 monitoring sites of mixed spatial data on topography, soils and stream hydrography. Calibration results explain approximately 95.96% (R2) of the spatial variability in the natural logarithm mean annual SS flux (kg km-2 yr-1) and display relatively small prediction errors at the 31 monitoring stations. Results show that developing-land is associated with the largest sediment yield at around 1006.27 kg km-2 yr-1, followed by agricultural-land (234.21 kg km-2 yr-1). Estimation of incremental yields shows that 35.11% comes from agricultural lands, 23.42% from forested lands, 22.91% from developing lands, and 18.56% from stream channels. The results of this study improve our understanding of sediments production and transportation in the Ishikari River Basin in general, which will benefit both the scientific and the management community in safeguarding water resources.

Assimilation of SMOS Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2016-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm(sub 3 cm(sub -3). These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve.

Assimilation of SMOS Retrievals in the Land Information System

PubMed Central

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2018-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm3 cm−3. These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve. PMID:29367795

Simulation of the spatial stresses due to territorial land development on Yellow River Delta Nature Reserve using a GIS-based assessment model.

PubMed

Zhang, Baolei; Zhang, Qiaoyun; Feng, Qingyu; Cui, Bohao; Zhang, Shumin

2017-07-01

This study aimed at assessing the stresses from land development in or around Yellow River Delta Nature Reserve (YRDNR) and identifying the impacted areas. Major land development types (reservoirs, pond, aquafarm, salt pan, road, residential land, industry land, farming land, and fishing land) in or around the YRDNR from 1995 to 2014 were identified using spatial data sets derived from remote sensing imageries. The spatial stresses were simulated by considering disturbance due to land development activities and accessibility of disturbance using a geographic information system based model. The stresses were then used to identify the impacted area by land development (IALD). The results indicated that main increasing land development types in the study area from 1995 to 2014 were salt pan and construction land. The 98.2% of expanded land development area and 93.7% of increased pump number showed a good control of reserve function zone on land development spread. The spatial stress values and percentages of IALD increased from 1995 to 2014, and IALD percentage exceeded 50% for both parts of YRDNR in 2014. The results of this study also provided the information that detailed planning of the YRDNR (2014-2020) could decrease the spatial stress and IALD percentage of the whole YRDNR on the condition that the area of land development activities increased by 24.4 km 2 from 2014 to 2020. Effective measures should be taken to protect such areas from being further disturbed in order to achieve the goal of a more effective conservation of the YRDNR, and attention should be paid to the disordered land development activities in or around the natural reserves.

An Assessment of Flap and Main Landing Gear Noise Abatement Concepts

NASA Technical Reports Server (NTRS)

Khorrami, Mehdi R.; Humphreys, William M., Jr.; Lockard, David P.

2015-01-01

A detailed assessment of the acoustic performance of several noise reduction concepts for aircraft flaps and landing gear is presented. Consideration is given to the best performing concepts within the suite of technologies that were evaluated in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel using an 18 percent scale, semi-span, high-fidelity Gulfstream aircraft model as a test bed. Microphone array measurements were obtained with the model in a landing configuration (flap deflected 39 degrees and the main landing gear deployed or retracted). The effectiveness of each concept over the range of pitch angles, speeds, and directivity angles tested is presented. Comparison of the acoustic spectra, obtained from integration of the beamform maps between the untreated baseline and treated configurations, clearly demonstrates that the flap and gear concepts maintain noise reduction benefits over the entire range of the directivity angles tested.

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 influences of land use and land cover on climate; an analysis of the Washington-Baltimore area that couples remote sensing with numerical simulation

USGS Publications Warehouse

Pease, R.W.; Jenner, C.B.; Lewis, J.E.

1980-01-01

The Sun drives the atmospheric heat engine by warming the terrestrial surface which in turn warms the atmosphere above. Climate, therefore, is significantly controlled by complex interaction of energy flows near and at the terrestrial surface. When man alters this delicate energy balance by his use of the land, he may alter his climatic environment as well. Land use climatology has emerged as a discipline in which these energy interactions are studied; first, by viewing the spatial distributions of their surface manifestations, and second, by analyzing the energy exchange processes involved. Two new tools for accomplishing this study are presented: one that can interpret surface energy exchange processes from space, and another that can simulate the complex of energy transfers by a numerical simulation model. Use of a satellite-borne multispectral scanner as an imaging radiometer was made feasible by devising a gray-window model that corrects measurements made in space for the effects of the atmosphere in the optical path. The simulation model is a combination of mathematical models of energy transfer processes at or near the surface. Integration of these two analytical approaches was applied to the Washington-Baltimore area to coincide with the August 5, 1973, Skylab 3 overpass which provided data for constructing maps of the energy characteristics of the Earth's surface. The use of the two techniques provides insights into the relationship of climate to land use and land cover and in predicting alterations of climate that may result from alterations of the land surface.

Evaluation of the North American Land Data Assimilation System over the southern Great Plains during the warm season

NASA Astrophysics Data System (ADS)

Robock, Alan; Luo, Lifeng; Wood, Eric F.; Wen, Fenghua; Mitchell, Kenneth E.; Houser, Paul R.; Schaake, John C.; Lohmann, Dag; Cosgrove, Brian; Sheffield, Justin; Duan, Qingyun; Higgins, R. Wayne; Pinker, Rachel T.; Tarpley, J. Dan; Basara, Jeffery B.; Crawford, Kenneth C.

2003-11-01

North American Land Data Assimilation System (NLDAS) land surface models have been run for a retrospective period forced by atmospheric observations from the Eta analysis and actual precipitation and downward solar radiation to calculate land hydrology. We evaluated these simulations using in situ observations over the southern Great Plains for the periods of May-September of 1998 and 1999 by comparing the model outputs with surface latent, sensible, and ground heat fluxes at 24 Atmospheric Radiation Measurement/Cloud and Radiation Testbed stations and with soil temperature and soil moisture observations at 72 Oklahoma Mesonet stations. The standard NLDAS models do a fairly good job but with differences in the surface energy partition and in soil moisture between models and observations and among models during the summer, while they agree quite well on the soil temperature simulations. To investigate why, we performed a series of experiments accounting for differences between model-specified soil types and vegetation and those observed at the stations, and differences in model treatment of different soil types, vegetation properties, canopy resistance, soil column depth, rooting depth, root density, snow-free albedo, infiltration, aerodynamic resistance, and soil thermal diffusivity. The diagnosis and model enhancements demonstrate how the models can be improved so that they can be used in actual data assimilation mode.

Study on Spatio-Temporal Change of Ecological Land in Yellow River Delta Based on RS&GIS

NASA Astrophysics Data System (ADS)

An, GuoQiang

2018-06-01

The temporal and spatial variation of ecological land use and its current distribution were studied to provide reference for the protection of original ecological land and ecological environment in the Yellow River Delta. Using RS colour synthesis, supervised classification, unsupervised classification, vegetation index and other methods to monitor the impact of human activities on the original ecological land in the past 30 years; using GIS technology to analyse the statistical data and construct the model of original ecological land area index to study the ecological land distribution status. The results show that the boundary of original ecological land in the Yellow River Delta had been pushed toward the coastline at an average speed of 0.8km per year due to human activities. In the past 20 years, a large amount of original ecological land gradually transformed into artificial ecological land. In view of the evolution and status of ecological land in the Yellow River Delta, related local departments should adopt differentiated and focused protection measures to protect the ecological land of the Yellow River Delta.

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

USGS Publications Warehouse

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

2012-01-01

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

Land degradation assessment by geo-spatially modeling different soil erodibility equations in a semi-arid catchment.

PubMed

Saygın, Selen Deviren; Basaran, Mustafa; Ozcan, Ali Ugur; Dolarslan, Melda; Timur, Ozgur Burhan; Yilman, F Ebru; Erpul, Gunay

2011-09-01

Land degradation by soil erosion is one of the most serious problems and environmental issues in many ecosystems of arid and semi-arid regions. Especially, the disturbed areas have greater soil detachability and transportability capacity. Evaluation of land degradation in terms of soil erodibility, by using geostatistical modeling, is vital to protect and reclaim susceptible areas. Soil erodibility, described as the ability of soils to resist erosion, can be measured either directly under natural or simulated rainfall conditions, or indirectly estimated by empirical regression models. This study compares three empirical equations used to determine the soil erodibility factor of revised universal soil loss equation prediction technology based on their geospatial performances in the semi-arid catchment of the Saraykoy II Irrigation Dam located in Cankiri, Turkey. A total of 311 geo-referenced soil samples were collected with irregular intervals from the top soil layer (0-10 cm). Geostatistical analysis was performed with the point values of each equation to determine its spatial pattern. Results showed that equations that used soil organic matter in combination with the soil particle size better agreed with the variations in land use and topography of the catchment than the one using only the particle size distribution. It is recommended that the equations which dynamically integrate soil intrinsic properties with land use, topography, and its influences on the local microclimates, could be successfully used to geospatially determine sites highly susceptible to water erosion, and therefore, to select the agricultural and bio-engineering control measures needed.

Why the predictions for monsoon rainfall fail?

NASA Astrophysics Data System (ADS)

Lee, J.

2016-12-01

To be in line with the Global Land/Atmosphere System Study (GLASS) of the Global Energy and Water Cycle Experiment (GEWEX) international research scheme, this study discusses classical arguments about the feedback mechanisms between land surface and precipitation to improve the predictions of African monsoon rainfall. In order to clarify the impact of antecedent soil moisture on subsequent rainfall evolution, several data sets will be presented. First, in-situ soil moisture field measurements acquired by the AMMA field campaign will be shown together with rain gauge data. This data set will validate various model and satellite data sets such as NOAH land surface model, TRMM rainfall, CMORPH rainfall and HadGEM climate models, SMOS soil moisture. To relate soil moisture with precipitation, two approaches are employed: one approach makes a direct comparison between the spatial distributions of soil moisture as an absolute value and rainfall, while the other measures a temporal evolution of the consecutive dry days (i.e. a relative change within the same soil moisture data set over time) and rainfall occurrences. Consecutive dry days shows consistent results of a negative feedback between soil moisture and rainfall across various data sets, contrary to the direct comparison of soil moisture state. This negative mechanism needs attention, as most climate models usually focus on a positive feedback only. The approach of consecutive dry days takes into account the systematic errors in satellite observations, reminding us that it may cause the misinterpretation to directly compare model with satellite data, due to their difference in data retrievals. This finding is significant, as the climate indices employed by the Intergovernmental Panel on Climate Change (IPCC) modelling archive are based on the atmospheric variable rathr than land.

Ozone distributions over southern Lake Michigan: comparisons between ferry-based observations, shoreline-based DOAS observations and model forecasts

NASA Astrophysics Data System (ADS)

Cleary, P. A.; Fuhrman, N.; Schulz, L.; Schafer, J.; Fillingham, J.; Bootsma, H.; McQueen, J.; Tang, Y.; Langel, T.; McKeen, S.; Williams, E. J.; Brown, S. S.

2015-05-01

Air quality forecast models typically predict large summertime ozone abundances over water relative to land in the Great Lakes region. While each state bordering Lake Michigan has dedicated monitoring systems, offshore measurements have been sparse, mainly executed through specific short-term campaigns. This study examines ozone abundances over Lake Michigan as measured on the Lake Express ferry, by shoreline differential optical absorption spectroscopy (DOAS) observations in southeastern Wisconsin and as predicted by the Community Multiscale Air Quality (CMAQ) model. From 2008 to 2009 measurements of O3, SO2, NO2 and formaldehyde were made in the summertime by DOAS at a shoreline site in Kenosha, WI. From 2008 to 2010 measurements of ambient ozone were conducted on the Lake Express, a high-speed ferry that travels between Milwaukee, WI, and Muskegon, MI, up to six times daily from spring to fall. Ferry ozone observations over Lake Michigan were an average of 3.8 ppb higher than those measured at shoreline in Kenosha, with little dependence on position of the ferry or temperature and with greatest differences during evening and night. Concurrent 1-48 h forecasts from the CMAQ model in the upper Midwestern region surrounding Lake Michigan were compared to ferry ozone measurements, shoreline DOAS measurements and Environmental Protection Agency (EPA) station measurements. The bias of the model O3 forecast was computed and evaluated with respect to ferry-based measurements. Trends in the bias with respect to location and time of day were explored showing non-uniformity in model bias over the lake. Model ozone bias was consistently high over the lake in comparison to land-based measurements, with highest biases for 25-48 h after initialization.

Aquifer-System Compaction and Land Subsidence: Measurements, Analyses, and Simulations-the Holly Site, Edwards Air Force Base, Antelope Valley, California

USGS Publications Warehouse

Sneed, Michelle; Galloway, Devin L.

2000-01-01

Land subsidence resulting from ground-water-level declines has long been recognized as a problem in Antelope Valley, California. At Edwards Air Force Base (EAFB), ground-water extractions have caused more than 150 feet of water-level decline, resulting in nearly 4 feet of subsidence. Differential land subsidence has caused sinklike depressions and earth fissures and has accelerated erosion of the playa lakebed surface of Rogers Lake at EAFB, adversely affecting the runways on the lakebed which are used for landing aircraft such as the space shuttles. Since 1990, about 0.4 foot of aquifer-system compaction has been measured at a deep (840 feet) borehole extensometer (Holly site) at EAFB. More than 7 years of paired ground-water-level and aquifer-system compaction measurements made at the Holly site were analyzed for this study. Annually, seasonal water-level fluctuations correspond to steplike variations in aquifer-system compaction; summer water-level drawdowns are associated with larger rates of compaction, and winter water-level recoveries are associated with smaller rates of compaction. The absence of aquifer-system expansion during recovery is consistent with the delayed drainage and resultant delayed, or residual, compaction of thick aquitards. A numerical one-dimensional MODFLOW model of aquitard drainage was used to refine estimates of aquifer-system hydraulic parameters that control compaction and to predict potential future compaction at the Holly site. The analyses and simulations of aquifer-system compaction are based on established theories of aquitard drainage. Historical ground-water-level and land-subsidence data collected near the Holly site were used to constrain simulations of aquifer-system compaction and land subsidence at the site for the period 1908?90, and ground-water-level and aquifer- system compaction measurements collected at the Holly site were used to constrain the model for the period 1990?97. Model results indicate that two thick aqui- tards, which total 129 feet or about half the aggregate thickness of all the aquitards penetrated by the Holly boreholes, account for most (greater than 99 percent) of the compaction measured at the Holly site during the period 1990?97. The results of three scenarios of future water-level changes indicate that these two thick aquitards account for most of the future compaction. The results also indicate that if water levels decline to about 30 feet below the 1997 water levels an additional 1.7 feet of compaction may occur during the next 30 years. If water levels remain at 1997 levels, the model predicts that only 0.8 foot of compaction may occur during the same period, and even if water levels recover to about 30 feet above 1997 water levels, another 0.5 foot of compaction may occur in the next 30 years. In addition, only a portion of the compaction that ultimately will occur likely will occur within the next 30 years; therefore, the residual compaction and associated land subsidence attributed to slowly equilibrating aquitards is important to consider in the long-term management of land and water resources at EAFB.

Evaluation of the North American Land Data Assimilation System over the Southern Great Plains during the warm season

NASA Astrophysics Data System (ADS)

Robock, A.; Luo, L.; Wood, E. F.; Wen, F.; Mitchell, K. E.; Houser, P. R.; Schaake, J. C.; Nldas Team

2003-04-01

To conduct land data assimilation, validated land surface models are needed. The first step in the North American Land Data Assimilation System (NLDAS) is to evaluate four such state-of-the-art models. These models (VIC, Noah, Mosaic, and Sacramento) have been run for a retrospective period forced by atmospheric observations from the Eta analysis and actual precipitation and downward solar radiation (on a 1/8 degree North American grid) to calculate land hydrology. First we show that the forcing data set agrees very well with local observations and that simulations forced with local observations differ little from those forced with the NLDAS forcing data set. Then we evaluated the simulations using in situ observations over the Southern Great Plains for the periods of May-September of 1998 and 1999 by comparing the model outputs with surface latent, sensible, and ground heat fluxes at 24 Atmospheric Radiation Measurement/Cloud and Radiation Testbed stations and with soil temperature and soil moisture observations at 72 Oklahoma Mesonet stations. The standard NLDAS models do a fairly good job but with differences in the surface energy partition and in soil moisture between models and observations and among models during the summer, while they agree quite well on the soil temperature simulations. To investigate why, we performed a series of experiments accounting for differences between model-specified soil types and vegetation and those observed at the stations, and differences in model treatment of different soil types, vegetation properties, canopy resistance, soil column depth, rooting depth, root density, snow-free albedo, infiltration, aerodynamic resistance, and soil thermal diffusivity. The diagnosis and model enhancements demonstrate how the models can be improved so that they can be used in actual data assimilation mode.

Characterization of Flap Edge Noise Radiation from a High-Fidelity Airframe Model

NASA Technical Reports Server (NTRS)

Humphreys, William M., Jr.; Khorrami, Mehdi R.; Lockard, David P.; Neuhart, Dan H.; Bahr, Christopher J.

2015-01-01

The results of an experimental study of the noise generated by a baseline high-fidelity airframe model are presented. The test campaign was conducted in the open-jet test section of the NASA Langley 14- by 22-foot Subsonic Tunnel on an 18%-scale, semi-span Gulfstream airframe model incorporating a trailing edge flap and main landing gear. Unsteady surface pressure measurements were obtained from a series of sensors positioned along the two flap edges, and far field acoustic measurements were obtained using a 97-microphone phased array that viewed the pressure side of the airframe. The DAMAS array deconvolution method was employed to determine the locations and strengths of relevant noise sources in the vicinity of the flap edges and the landing gear. A Coherent Output Power (COP) spectral method was used to couple the unsteady surface pressures measured along the flap edges with the phased array output. The results indicate that outboard flap edge noise is dominated by the flap bulb seal cavity with very strong COP coherence over an approximate model-scale frequency range of 1 to 5 kHz observed between the array output and those unsteady pressure sensors nearest the aft end of the cavity. An examination of experimental COP spectra for the inboard flap proved inconclusive, most likely due to a combination of coherence loss caused by decorrelation of acoustic waves propagating through the thick wind tunnel shear layer and contamination of the spectra by tunnel background noise at lower frequencies. Directivity measurements obtained from integration of DAMAS pressure-squared values over defined geometric zones around the model show that the baseline flap and landing gear are only moderately directional as a function of polar emission angle.

Relationship between jump landing kinematics and peak ACL force during a jump in downhill skiing: a simulation study.

PubMed

Heinrich, D; van den Bogert, A J; Nachbauer, W

2014-06-01

Recent data highlight that competitive skiers face a high risk of injuries especially during off-balance jump landing maneuvers in downhill skiing. The purpose of the present study was to develop a musculo-skeletal modeling and simulation approach to investigate the cause-and-effect relationship between a perturbed landing position, i.e., joint angles and trunk orientation, and the peak force in the anterior cruciate ligament (ACL) during jump landing. A two-dimensional musculo-skeletal model was developed and a baseline simulation was obtained reproducing measurement data of a reference landing movement. Based on the baseline simulation, a series of perturbed landing simulations (n = 1000) was generated. Multiple linear regression was performed to determine a relationship between peak ACL force and the perturbed landing posture. Increased backward lean, hip flexion, knee extension, and ankle dorsiflexion as well as an asymmetric position were related to higher peak ACL forces during jump landing. The orientation of the trunk of the skier was identified as the most important predictor accounting for 60% of the variance of the peak ACL force in the simulations. Teaching of tactical decisions and the inclusion of exercise regimens in ACL injury prevention programs to improve trunk control during landing motions in downhill skiing was concluded. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Estimating of the impact of land use changes using the conceptual hydrological model THESEUS??a case study

NASA Astrophysics Data System (ADS)

Wegehenkel, Martin

As a result of a new agricultural funding policy established in 1992 by the European Community, it was assumed that up to 15-20% of arable land would have been set aside in the next years in the new federal states of north-eastern Germany, for example, Brandenburg. As one potential land use option, afforestation of these set aside areas was discussed to obtain deciduous forests. Since the mean annual precipitation in north-eastern Germany, Brandenburg is relatively low (480-530 mm y -1), an increase in interception and evapotranspiration loss by forests compared to arable land would lead to a reduction in ground water recharge. Experimental evidence to determine effects of such land use changes are rarely available. Therefore, there is a need for indirect methods to estimate the impact of afforestation on the water balance of catchments. In this paper, a conceptual hydrological model was verified and calibrated in two steps using data from the Stobber-catchment located in Brandenburg. In the first step, model outputs like daily evapotranspiration rates and soil water contents were verified on the basis of experimental data sets from two test locations. One test site with the land use arable land was located within the Stobber-catchment. The other test site with pine forest was located near by the catchment. In the second step, the model was used to estimate the impact of afforestation on catchment water balance and discharge. For that purpose, the model was calibrated against daily discharge measurements for the period 1995-1997. For a simple afforestation scenario, it was assumed that the area of forest increases from 34% up to 80% of the catchment area. The impact of this change in forest cover proportion was analyzed using the calibrated model. In case of increasing the proportion of forest cover in the catchment due to the scenario afforestation, the model predicts a reduction in discharge and an increase in evapotranspiration.

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.

Estimation of land photosynthetically active radiation in clear sky using MODIS atmosphere and land products

NASA Astrophysics Data System (ADS)

Xie, Xiaoping; Gao, Wei; Gao, Zhiqiang

2008-08-01

Photosynthetically active radiation (PAR) is an essential parameter in vegetation growth model and soil carbon sequestration models. A method is presented with which instantaneous PAR can be calculated with high accuracy from Moderate Resolution Imaging Spectroradiometer (MODIS) atmosphere and land products. The method is based on a simplification of the general radiative transfer equation, which considers five major processes of attenuation of solar radiation: Rayleigh scattering, absorption by ozone and water vapor, aerosol scattering, multiply reflectance between surface and atmosphere. Comparing 108 retrieveled results to filed measured PAR in Yucheng station of Chinese Ecosystem Research Network (CERN) in 2006, and the r-square of 0.855 indicates that the computed results can interpret actual PAR well.

Utilizing remote sensing of Thematic Mapper data to improve our understanding of estuarine processes and their influence on the productivity of estuarine-dependent fisheries

NASA Technical Reports Server (NTRS)

Browder, J. A.; May, L. N., Jr.; Rosenthal, A.; Baumann, R. H.; Gosselink, J. G.

1986-01-01

LANDSAT thematic mapper (TM) data are being used to refine and validate a stochastic spatial computer model to be applied to coastal resource management problems in Louisiana. Two major aspects of the research are: (1) the measurement of area of land (or emergent vegetation) and water and the length of the interface between land and water in TM imagery of selected coastal wetlands (sample marshes); and (2) the comparison of spatial patterns of land and water in the sample marshes of the imagery to that in marshes simulated by a computer model. In addition to activities in these two areas, the potential use of a published autocorrelation statistic is analyzed.

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.

Land-atmosphere interaction patterns in southeastern South America using satellite products and climate models

NASA Astrophysics Data System (ADS)

Spennemann, P. C.; Salvia, M.; Ruscica, R. C.; Sörensson, A. A.; Grings, F.; Karszenbaum, H.

2018-02-01

In regions of strong Land-Atmosphere (L-A) interaction, soil moisture (SM) conditions can impact the atmosphere through modulating the land surface fluxes. The importance of the identification of L-A interaction regions lies in the potential improvement of the weather/seasonal forecast and the better understanding of the physical mechanisms involved. This study aims to compare the terrestrial segment of the L-A interaction from satellite products and climate models, motivated by previous modeling studies pointing out southeastern South America (SESA) as a L-A hotspot during austral summer. In addition, the L-A interaction under dry or wet anomalous conditions over SESA is analyzed. To identify L-A hotspots the AMSRE-LPRM SM and MODIS land surface temperature products; coupled climate models and uncoupled land surface models were used. SESA highlights as a strong L-A interaction hotspot when employing different metrics, temporal scales and independent datasets, showing consistency between models and satellite estimations. Both AMSRE-LPRM bands (X and C) are consistent showing a strong L-A interaction hotspot over the Pampas ecoregion. Intensification and a larger spatial extent of the L-A interaction for dry summers was observed in both satellite products and models compared to wet summers. These results, which were derived from measured physical variables, are encouraging and promising for future studies analyzing L-A interactions. L-A interaction analysis is proposed here as a meeting point between remote sensing and climate modelling communities of Argentina, within a region with the highest agricultural and livestock production of the continent, but with an important lack of in-situ SM observations.

Integrated cost-effectiveness analysis of agri-environmental measures for water quality.

PubMed

Balana, Bedru B; Jackson-Blake, Leah; Martin-Ortega, Julia; Dunn, Sarah

2015-09-15

This paper presents an application of integrated methodological approach for identifying cost-effective combinations of agri-environmental measures to achieve water quality targets. The methodological approach involves linking hydro-chemical modelling with economic costs of mitigation measures. The utility of the approach was explored for the River Dee catchment in North East Scotland, examining the cost-effectiveness of mitigation measures for nitrogen (N) and phosphorus (P) pollutants. In-stream nitrate concentration was modelled using the STREAM-N and phosphorus using INCA-P model. Both models were first run for baseline conditions and then their effectiveness for changes in land management was simulated. Costs were based on farm income foregone, capital and operational expenditures. The costs and effects data were integrated using 'Risk Solver Platform' optimization in excel to produce the most cost-effective combination of measures by which target nutrient reductions could be attained at a minimum economic cost. The analysis identified different combination of measures as most cost-effective for the two pollutants. An important aspect of this paper is integration of model-based effectiveness estimates with economic cost of measures for cost-effectiveness analysis of land and water management options. The methodological approach developed is not limited to the two pollutants and the selected agri-environmental measures considered in the paper; the approach can be adapted to the cost-effectiveness analysis of any catchment-scale environmental management options. Copyright © 2015 Elsevier Ltd. All rights reserved.

Validating modeled soil moisture with in-situ data for agricultural drought monitoring in West Africa

NASA Astrophysics Data System (ADS)

McNally, A.; Yatheendradas, S.; Jayanthi, H.; Funk, C. C.; Peters-Lidard, C. D.

2011-12-01

The declaration of famine in Somalia on July 21, 2011 highlights the need for regional hydroclimate analysis at a scale that is relevant for agropastoral drought monitoring. A particularly critical and robust component of such a drought monitoring system is a land surface model (LSM). We are currently enhancing the Famine Early Warning Systems Network (FEWS NET) monitoring activities by configuring a custom instance of NASA's Land Information System (LIS) called the FEWS NET Land Data Assimilation System (FLDAS). Using the LIS Noah LSM, in-situ measurements, and remotely sensed data, we focus on the following question: How can Noah be best parameterized to accurately simulate hydroclimate variables associated with crop performance? Parameter value testing and validation is done by comparing modeled soil moisture against fortuitously available in-situ soil moisture observations in the West Africa. Direct testing and application of the FLDAS over African agropastoral locations is subject to some issues: [1] In many regions that are vulnerable to food insecurity ground based measurements of precipitation, evapotranspiration and soil moisture are sparse or non-existent, [2] standard landcover classes (e.g., the University of Maryland 5 km dataset), do not include representations of specific agricultural crops with relevant parameter values, and phenologies representing their growth stages from the planting date and [3] physically based land surface models and remote sensing rain data might still need to be calibrated or bias-corrected for the regions of interest. This research aims to address these issues by focusing on sites in the West African countries of Mali, Niger, and Benin where in-situ rainfall and soil moisture measurements are available from the African Monsoon Multidisciplinary Analysis (AMMA). Preliminary results from model experiments over Southern Malawi, validated with Normalized Difference Vegetation Index (NDVI) and maize yield data, show that the ability to detect a drought signal in modeled soil moisture and actual evapotranspiration was sensitive to parameters like minimum stomatal resistance, green vegetation fraction, and minimum threshold for transpiration stress. In addition to improving our understanding and representation of the land surface physics in agropastoral drought, this study moves us closer to confidently validating LSM estimates with remotely sensed data (e.g. MODIS NDVI), essential in regions that lack ground based measurements. Ultimately, these improved information products serve to better inform decision makers about seasonal food production and anticipate the need for relief, as well as guide climate change adaptation strategies, potentially saving millions of lives.

Environmental assessment of biofuel chains based on ecosystem modelling, including land-use change effects

NASA Astrophysics Data System (ADS)

Gabrielle, B.; Gagnaire, N.; Massad, R.; Prieur, V.; Python, Y.

2012-04-01

The potential greenhouse gas (GHG) savings resulting from the displacement of fossil energy sources by bioenergy mostly hinges on the uncertainty on the magnitude of nitrous oxide (N2O) emissions from arable soils occuring during feedstock production. These emissions are broadly related to fertilizer nitrogen input rates, but largely controlled by soil and climate factors which makes their estimation highly uncertain. Here, we set out to improve estimates of N2O emissions from bioenergy feedstocks by using ecosystem models and measurements and modeling of atmospheric N2O in the greater Paris (France) area. Ground fluxes were measured in two locations to assess the effect of soil type and management, crop type (including lignocellulosics such as triticale, switchgrass and miscanthus), and climate on N2O emission rates and dynamics. High-resolution maps of N2O emissions were generated over the Ile-de-France region (around Paris) with two ecosystem models using geographical databases on soils, weather data, land-use and crop management. The models were tested against ground flux measurements and the emission maps were fed into the atmospheric chemistry-transport model CHIMERE. The maps were tested by comparing the CHIMERE simulations with time series of N2O concentrations measured at various heights above the ground in two locations in 2007. The emissions of N2O, as integrated over the region, were used in a life-cycle assessment of representative biofuel pathways: bioethanol from wheat and sugar-beet (1st generation), and miscanthus (2nd generation chain); bio-diesel from oilseed rape. Effects related to direct and indirect land-use changes (in particular on soil carbon stocks) were also included in the assessment based on various land-use scenarios and literature references. The potential deployment of miscanthus was simulated by assuming it would be grown on the current sugar-beet growing area in Ile-de-France, or by converting land currently under permanent fallow. Compared to the standard methodology currently used in LCA, based on fixed emissions for N2O, the use of model-derived estimates leads to a 10 to 40% reduction in the overall life-cycle GHG emissions of biofuels. This emphasizes the importance of regional factors in the relationship between agricultural inputs and emissions (altogether with biomass yields) in the outcome of LCAs. When excluding indirect land-use change effects (iLUC), 1st generation pathways enabled GHG savings ranging from 50 to 73% compared to fossile-derived equivalents, while this figure reached 88% for 2nd generation bioethanol from miscanthus. Including iLUC reduced the savings to less than 5% for bio-diesel from rapeseed, 10 to 45% for 1st generation bioethanol and to 60% for miscanthus. These figures apply to the year 2007 and should be extended to a larger number of years, but the magnitude of N2O emissions was similar between 2007, 2008 and 2009 over the Ile de France region.

Turbulence structure of the marine stable boundary layer over the Baltic Sea

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

Smedman, A.S.; Hoegstroem, U.

For more than half of the year the land surfaces surrounding the Baltic Sea is warmer than the sea surface, and the marine boundary layer over the Baltic is stable. Observations, at various sites in the Baltic Sea area during the last decade. also indicate frequent occurrence of low-level jets at the top of the stable boundary layer. In many cases the marine jet can be considered as an analogy in space to the evolution of the nocturnal jet with time. The frictional decoupling occurs when warm air over the land is flowing out over the sea. Data from twomore » areas together with model simulations are used in this study to characterize turbulence structure in the marine boundary layer. The measurements include profiles of wind and temperature on towers situated at two isolated islands, together with turbulence recordings and aircraft measurements. Also wave height and water surface temperature have been measured. The model simulations are performed with a second-order closure model.« less

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

NASA Astrophysics Data System (ADS)

Ellis, E. C.

2006-12-01

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

Uncertainty in BMP evaluation and optimization for watershed management

NASA Astrophysics Data System (ADS)

Chaubey, I.; Cibin, R.; Sudheer, K.; Her, Y.

2012-12-01

Use of computer simulation models have increased substantially to make watershed management decisions and to develop strategies for water quality improvements. These models are often used to evaluate potential benefits of various best management practices (BMPs) for reducing losses of pollutants from sources areas into receiving waterbodies. Similarly, use of simulation models in optimizing selection and placement of best management practices under single (maximization of crop production or minimization of pollutant transport) and multiple objective functions has increased recently. One of the limitations of the currently available assessment and optimization approaches is that the BMP strategies are considered deterministic. Uncertainties in input data (e.g. precipitation, streamflow, sediment, nutrient and pesticide losses measured, land use) and model parameters may result in considerable uncertainty in watershed response under various BMP options. We have developed and evaluated options to include uncertainty in BMP evaluation and optimization for watershed management. We have also applied these methods to evaluate uncertainty in ecosystem services from mixed land use watersheds. In this presentation, we will discuss methods to to quantify uncertainties in BMP assessment and optimization solutions due to uncertainties in model inputs and parameters. We have used a watershed model (Soil and Water Assessment Tool or SWAT) to simulate the hydrology and water quality in mixed land use watershed located in Midwest USA. The SWAT model was also used to represent various BMPs in the watershed needed to improve water quality. SWAT model parameters, land use change parameters, and climate change parameters were considered uncertain. It was observed that model parameters, land use and climate changes resulted in considerable uncertainties in BMP performance in reducing P, N, and sediment loads. In addition, climate change scenarios also affected uncertainties in SWAT simulated crop yields. Considerable uncertainties in the net cost and the water quality improvements resulted due to uncertainties in land use, climate change, and model parameter values.

The contribution of future agricultural trends in the US Midwest to global climate change mitigation

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

Thomson, Allison M.; Kyle, G. Page; Zhang, Xuesong

2014-01-19

Land use change is a complex response to changing environmental and socioeconomic systems. Historical drivers of land use change include changes in the natural resource availability of a region, changes in economic conditions for production of certain products and changing policies. Most recently, introduction of policy incentives for biofuel production have influenced land use change in the US Midwest, leading to concerns that bioenergy production systems may compete with food production and land conservation. Here we explore how land use may be impacted by future climate mitigation measures by nesting a high resolution agricultural model (EPIC – Environmental Policy Indicatormore » Climate) for the US Midwest within a global integrated assessment model (GCAM – Global Change Assessment Model). This approach is designed to provide greater spatial resolution and detailed agricultural practice information by focusing on the climate mitigation potential of agriculture and land use in a specific region, while retaining the global economic context necessary to understand the far ranging effects of climate mitigation targets. We find that until the simulated carbon prices are very high, the US Midwest has a comparative advantage in producing traditional food and feed crops over bioenergy crops. Overall, the model responds to multiple pressures by adopting a mix of future responses. We also find that the GCAM model is capable of simulations at multiple spatial scales and agricultural technology resolution, which provides the capability to examine regional response to global policy and economic conditions in the context of climate mitigation.« less

Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

DOE PAGES

Calvin, Kate; Fisher-Vanden, Karen

2017-10-27

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparisonmore » between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between - 12% and + 15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.« less

Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

NASA Astrophysics Data System (ADS)

Calvin, Kate; Fisher-Vanden, Karen

2017-11-01

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparison between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between -12% and +15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.

Quantifying the indirect impacts of climate on agriculture: an inter-method comparison

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

Calvin, Kate; Fisher-Vanden, Karen

Climate change and increases in CO2 concentration affect the productivity of land, with implications for land use, land cover, and agricultural production. Much of the literature on the effect of climate on agriculture has focused on linking projections of changes in climate to process-based or statistical crop models. However, the changes in productivity have broader economic implications that cannot be quantified in crop models alone. How important are these socio-economic feedbacks to a comprehensive assessment of the impacts of climate change on agriculture? In this paper, we attempt to measure the importance of these interaction effects through an inter-method comparisonmore » between process models, statistical models, and integrated assessment model (IAMs). We find the impacts on crop yields vary widely between these three modeling approaches. Yield impacts generated by the IAMs are 20%-40% higher than the yield impacts generated by process-based or statistical crop models, with indirect climate effects adjusting yields by between - 12% and + 15% (e.g. input substitution and crop switching). The remaining effects are due to technological change.« less

Mars Pathfinder meteorological observations on the basis of results of an atmospheric global circulation model

NASA Technical Reports Server (NTRS)

Forget, Francois; Hourdin, F.; Talagrand, O.

1994-01-01

The Mars Pathfinder Meteorological Package (ASI/MET) will measure the local pressure, temperature, and winds at its future landing site, somewhere between the latitudes 0 deg N and 30 deg N. Comparable measurements have already been obtained at the surface of Mars by the Viking Landers at 22 deg N (VL1) and 48 deg N (VL2), providing much useful information on the martian atmosphere. In particular the pressure measurements contain very instructive information on the global atmospheric circulation. At the Laboratoire de Meteorologie Dynamique (LMD), we have analyzed and simulated these measurements with a martian atmospheric global circulation model (GCM), which was the first to simulate the martian atmospheric circulation over more than 1 year. The model is able to reproduce rather accurately many observed features of the martian atmosphere, including the long- and short-period oscillations of the surface pressure observed by the Viking landers. From a meteorological point of view, we think that a landing site located near or at the equator would be an interesting choice.

Land use regression modeling of ultrafine particles, ozone, nitrogen oxides and markers of particulate matter pollution in Augsburg, Germany.

PubMed

Wolf, Kathrin; Cyrys, Josef; Harciníková, Tatiana; Gu, Jianwei; Kusch, Thomas; Hampel, Regina; Schneider, Alexandra; Peters, Annette

2017-02-01

Important health relevance has been suggested for ultrafine particles (UFP) and ozone, but studies on long-term effects are scarce, mainly due to the lack of appropriate spatial exposure models. We designed a measurement campaign to develop land use regression (LUR) models to predict the spatial variability focusing on particle number concentration (PNC) as indicator for UFP, ozone and several other air pollutants in the Augsburg region, Southern Germany. Three bi-weekly measurements of PNC, ozone, particulate matter (PM 10 , PM 2.5 ), soot (PM 2.5 abs) and nitrogen oxides (NO x , NO 2 ) were performed at 20 sites in 2014/15. Annual average concentration were calculated and temporally adjusted by measurements from a continuous background station. As geographic predictors we offered several traffic and land use variables, altitude, population and building density. Models were validated using leave-one-out cross-validation. Adjusted model explained variance (R 2 ) was high for PNC and ozone (0.89 and 0.88). Cross-validation adjusted R 2 was slightly lower (0.82 and 0.81) but still indicated a very good fit. LUR models for other pollutants performed well with adjusted R 2 between 0.68 (PM coarse ) and 0.94 (NO 2 ). Contrary to previous studies, ozone showed a moderate correlation with NO 2 (Pearson's r=-0.26). PNC was moderately correlated with ozone and PM 2.5 , but highly correlated with NO x (r=0.91). For PNC and NO x , LUR models comprised similar predictors and future epidemiological analyses evaluating health effects need to consider these similarities. Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluation of NASA's Carbon Monitoring System (CMS) Flux Pilot: Terrestrial CO2 Fluxes

NASA Astrophysics Data System (ADS)

Fisher, J. B.; Polhamus, A.; Bowman, K. W.; Collatz, G. J.; Potter, C. S.; Lee, M.; Liu, J.; Jung, M.; Reichstein, M.

2011-12-01

NASA's Carbon Monitoring System (CMS) flux pilot project combines NASA's Earth System models in land, ocean and atmosphere to track surface CO2 fluxes. The system is constrained by atmospheric measurements of XCO2 from the Japanese GOSAT satellite, giving a "big picture" view of total CO2 in Earth's atmosphere. Combining two land models (CASA-Ames and CASA-GFED), two ocean models (ECCO2 and NOBM) and two atmospheric chemistry and inversion models (GEOS-5 and GEOS-Chem), the system brings together the stand-alone component models of the Earth System, all of which are run diagnostically constrained by a multitude of other remotely sensed data. Here, we evaluate the biospheric land surface CO2 fluxes (i.e., net ecosystem exchange, NEE) as estimated from the atmospheric flux inversion. We compare against the prior bottom-up estimates (e.g., the CASA models) as well. Our evaluation dataset is the independently derived global wall-to-wall MPI-BGC product, which uses a machine learning algorithm and model tree ensemble to "scale-up" a network of in situ CO2 flux measurements from 253 globally-distributed sites in the FLUXNET network. The measurements are based on the eddy covariance method, which uses observations of co-varying fluxes of CO2 (and water and energy) from instruments on towers extending above ecosystem canopies; the towers integrate fluxes over large spatial areas (~1 km2). We present global maps of CO2 fluxes and differences between products, summaries of fluxes by TRANSCOM region, country, latitude, and biome type, and assess the time series, including timing of minimum and maximum fluxes. This evaluation shows both where the CMS is performing well, and where improvements should be directed in further work.

Combined measurement and modeling of the hydrological impact of hydraulic redistribution using CLM4.5 at eight AmeriFlux sites

NASA Astrophysics Data System (ADS)

Fu, Congsheng; Wang, Guiling; Goulden, Michael L.; Scott, Russell L.; Bible, Kenneth; Cardon, Zoe G.

2016-05-01

Effects of hydraulic redistribution (HR) on hydrological, biogeochemical, and ecological processes have been demonstrated in the field, but the current generation of standard earth system models does not include a representation of HR. Though recent studies have examined the effect of incorporating HR into land surface models, few (if any) have done cross-site comparisons for contrasting climate regimes and multiple vegetation types via the integration of measurement and modeling. Here, we incorporated the HR scheme of Ryel et al. (2002) into the NCAR Community Land Model Version 4.5 (CLM4.5), and examined the ability of the resulting hybrid model to capture the magnitude of HR flux and/or soil moisture dynamics from which HR can be directly inferred, to assess the impact of HR on land surface water and energy budgets, and to explore how the impact may depend on climate regimes and vegetation conditions. Eight AmeriFlux sites with contrasting climate regimes and multiple vegetation types were studied, including the Wind River Crane site in Washington State, the Santa Rita Mesquite savanna site in southern Arizona, and six sites along the Southern California Climate Gradient. HR flux, evapotranspiration (ET), and soil moisture were properly simulated in the present study, even in the face of various uncertainties. Our cross-ecosystem comparison showed that the timing, magnitude, and direction (upward or downward) of HR vary across ecosystems, and incorporation of HR into CLM4.5 improved the model-measurement matches of evapotranspiration, Bowen ratio, and soil moisture particularly during dry seasons. Our results also reveal that HR has important hydrological impact in ecosystems that have a pronounced dry season but are not overall so dry that sparse vegetation and very low soil moisture limit HR.

Local Scale Radiobrightness Modeling During the Intensive Observing Period-4 of the Cold Land Processes Experiment-1

NASA Astrophysics Data System (ADS)

Kim, E.; Tedesco, M.; de Roo, R.; England, A. W.; Gu, H.; Pham, H.; Boprie, D.; Graf, T.; Koike, T.; Armstrong, R.; Brodzik, M.; Hardy, J.; Cline, D.

2004-12-01

The NASA Cold Land Processes Field Experiment (CLPX-1) was designed to provide microwave remote sensing observations and ground truth for studies of snow and frozen ground remote sensing, particularly issues related to scaling. CLPX-1 was conducted in 2002 and 2003 in Colorado, USA. One of the goals of the experiment was to test the capabilities of microwave emission models at different scales. Initial forward model validation work has concentrated on the Local-Scale Observation Site (LSOS), a 0.8~ha study site consisting of open meadows separated by trees where the most detailed measurements were made of snow depth and temperature, density, and grain size profiles. Results obtained in the case of the 3rd Intensive Observing Period (IOP3) period (February, 2003, dry snow) suggest that a model based on Dense Medium Radiative Transfer (DMRT) theory is able to model the recorded brightness temperatures using snow parameters derived from field measurements. This paper focuses on the ability of forward DMRT modelling, combined with snowpack measurements, to reproduce the radiobrightness signatures observed by the University of Michigan's Truck-Mounted Radiometer System (TMRS) at 19 and 37~GHz during the 4th IOP (IOP4) in March, 2003. Unlike in IOP3, conditions during IOP4 include both wet and dry periods, providing a valuable test of DMRT model performance. In addition, a comparison will be made for the one day of coincident observations by the University of Tokyo's Ground-Based Microwave Radiometer-7 (GBMR-7) and the TMRS. The plot-scale study in this paper establishes a baseline of DMRT performance for later studies at successively larger scales. And these scaling studies will help guide the choice of future snow retrieval algorithms and the design of future Cold Lands observing systems.

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

NASA Astrophysics Data System (ADS)

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

2002-12-01

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

Inclusion of Solar Elevation Angle in Land Surface Albedo Parameterization Over Bare Soil Surface.

PubMed

Zheng, Zhiyuan; Wei, Zhigang; Wen, Zhiping; Dong, Wenjie; Li, Zhenchao; Wen, Xiaohang; Zhu, Xian; Ji, Dong; Chen, Chen; Yan, Dongdong

2017-12-01

Land surface albedo is a significant parameter for maintaining a balance in surface energy. It is also an important parameter of bare soil surface albedo for developing land surface process models that accurately reflect diurnal variation characteristics and the mechanism behind the solar spectral radiation albedo on bare soil surfaces and for understanding the relationships between climate factors and spectral radiation albedo. Using a data set of field observations, we conducted experiments to analyze the variation characteristics of land surface solar spectral radiation and the corresponding albedo over a typical Gobi bare soil underlying surface and to investigate the relationships between the land surface solar spectral radiation albedo, solar elevation angle, and soil moisture. Based on both solar elevation angle and soil moisture measurements simultaneously, we propose a new two-factor parameterization scheme for spectral radiation albedo over bare soil underlying surfaces. The results of numerical simulation experiments show that the new parameterization scheme can more accurately depict the diurnal variation characteristics of bare soil surface albedo than the previous schemes. Solar elevation angle is one of the most important factors for parameterizing bare soil surface albedo and must be considered in the parameterization scheme, especially in arid and semiarid areas with low soil moisture content. This study reveals the characteristics and mechanism of the diurnal variation of bare soil surface solar spectral radiation albedo and is helpful in developing land surface process models, weather models, and climate models.

Airframe Noise from a Hybrid Wing Body Aircraft Configuration

NASA Technical Reports Server (NTRS)

Hutcheson, Florence V.; Spalt, Taylor B.; Brooks, Thomas F.; Plassman, Gerald E.

2016-01-01

A high fidelity aeroacoustic test was conducted in the NASA Langley 14- by 22-Foot Subsonic Tunnel to establish a detailed database of component noise for a 5.8% scale HWB aircraft configuration. The model has a modular design, which includes a drooped and a stowed wing leading edge, deflectable elevons, twin verticals, and a landing gear system with geometrically scaled wheel-wells. The model is mounted inverted in the test section and noise measurements are acquired at different streamwise stations from an overhead microphone phased array and from overhead and sideline microphones. Noise source distribution maps and component noise spectra are presented for airframe configurations representing two different approach flight conditions. Array measurements performed along the aircraft flyover line show the main landing gear to be the dominant contributor to the total airframe noise, followed by the nose gear, the inboard side-edges of the LE droop, the wing tip/LE droop outboard side-edges, and the side-edges of deployed elevons. Velocity dependence and flyover directivity are presented for the main noise components. Decorrelation effects from turbulence scattering on spectral levels measured with the microphone phased array are discussed. Finally, noise directivity maps obtained from the overhead and sideline microphone measurements for the landing gear system are provided for a broad range of observer locations.

Scoring Methods in the International Land Benchmarking (ILAMB) Package

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Atmospheric Constraints on Landing Site Selection

NASA Astrophysics Data System (ADS)

Kass, David M.; Schofield, J. T.

2001-01-01

The Martian atmosphere is a significant part of the environment that the Mars Exploration Rovers (MER) will encounter. As such, it imposes important constraints on where the rovers can and cannot land. Unfortunately, as there are no meteorological instruments on the rovers, there is little atmospheric science that can be accomplished, and no scientific preference for landing sites. The atmosphere constrains landing site selection in two main areas, the entry descent and landing (EDL) process and the survivability of the rovers on the surface. EDL is influenced by the density profile and boundary layer winds (up to altitudes of 5 to 10 km). Surface survivability involves atmospheric dust, temperatures and winds. During EDL, the atmosphere is used to slow the lander down, both ballistically and on the parachute. This limits the maximum elevation of the landing site to -1.3 km below the MOLA reference aeroid. The landers need to encounter a sufficiently dense atmosphere to be able to stop, and the deeper the landing site, the more column integrated atmosphere the lander can pass through before reaching the surface. The current limit was determined both by a desire to be able to reach the hematite region and by a set of atmosphere models we developed for EDL simulations. These are based on Thermal Emission Spectrometer (TES) atmospheric profile measurements, Ames Mars General Circulation Model (MGCM) results, and the 1-D Ames GCM radiative/convective model by J. Murphy. The latter is used for the near surface diurnal cycle. The current version of our model encompasses representative latitude bands, but we intend to make specific models for the final candidate landing sites to insure that they fall within the general envelope. The second constraint imposed on potential landing sites through the EDL process is the near surface wind. The wind in the lower approximately 5 km determines the horizontal velocity that the landers have when they land. Due to the mechanics of the landing process, the total velocity (including both the horizontal and vertical components) determines whether or not the landers are successful. Unfortunately, the landing system has no easy way to nullify any horizontal velocity imparted by the wind, so the landing sites selected need to have as little wind as possible. In addition to the mean wind velocity, the landing system is sensitive to vertical wind shear in the lowest kilometer or so. Wind shear can deflect the retro rockets (RADs) from their nominal vertical orientation producing unwanted horizontal spacecraft velocities. Both mean velocity and wind shear are dominated by the the local topography and other surface properties (in particular albedo and thermal inertia which control the surface temperature). This is seen even in simplified 2-D mesoscale models. The effects in a fully 3-D model are expected to he even more topographically dependent. In particular there is potential for wind channeling in canyons and other terrain features. Boundary layer winds and wind shear are currently being modeled based on terrestrial data and boundary layer scaling laws modified for Martian conditions. We hope to supplement this with mesoscale model results (from several sources) once the number of landing sites is reduced to a manageable number.

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

2012-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.

[Methodology of the description of atmospheric air pollution by nitrogen dioxide by land use regression method in Ekaterinburg].

PubMed

Antropov, K M; Varaksin, A N

2013-01-01

This paper provides the description of Land Use Regression (LUR) modeling and the result of its application in the study of nitrogen dioxide air pollution in Ekaterinburg. The paper describes the difficulties of the modeling for air pollution caused by motor vehicles exhaust, and the ways to address these challenges. To create LUR model of the NO2 air pollution in Ekaterinburg, concentrations of NO2 were measured, data on factors affecting air pollution were collected, a statistical analysis of the data were held. A statistical model of NO2 air pollution (coefficient of determination R2 = 0.70) and a map of pollution were created.

A new framework for modeling urban land expansion in peri-urban area by combining multi-source datasets and data assimilation

NASA Astrophysics Data System (ADS)

Zhang, Z.; Xiao, R.; Li, X.

2015-12-01

Peri-urban area is a new type region under the impacts of both rural Industrialization and the radiation of metropolitan during rapid urbanization. Due to its complex natural and social characteristics and unique development patterns, many problems such as environmental pollution and land use waste emerged, which became an urgent issue to be addressed. Study area in this paper covers three typical peri-urban districts (Pudong, Fengxian and Jinshan), which around the Shanghai inner city. By coupling cellular automata and multi-agent system model as the basic tools, this research focus on modelling the urban land expansion and driving mechanism in peri-urban area. The big data is aslo combined with the Bayesian maximum entropy method (BME) for spatiotemporal prediction of multi-source data, which expand the dataset of urban expansion models. Data assimilation method is used to optimize the parameters of the coupling model and minimize the uncertainty of observations, improving the precision of future simulation in peri-urban area. By setting quantitative parameters, the coupling model can effectively improve the simulation of the process of urban land expansion under different policies and management schemes, in order to provide scientificimplications for new urbanization strategy. In this research, we precise the urban land expansion simulation and prediction for peri-urban area, expand the scopes and selections of data acquisition measurements and methods, develop the new applications of the data assimilation method in geographical science, provide a new idea for understanding the inherent rules of urban land expansion, and give theoretical and practical support for the peri-urban area in urban planning and decision making.

Assessing ecosystem response to multiple disturbances and climate change in South Africa using ground- and satellite-based measurements and model

NASA Astrophysics Data System (ADS)

Kutsch, W. L.; Falge, E. M.; Brümmer, C.; Mukwashi, K.; Schmullius, C.; Hüttich, C.; Odipo, V.; Scholes, R. J.; Mudau, A.; Midgley, G.; Stevens, N.; Hickler, T.; Scheiter, S.; Martens, C.; Twine, W.; Iiyambo, T.; Bradshaw, K.; Lück, W.; Lenfers, U.; Thiel-Clemen, T.; du Toit, J.

2015-12-01

Sub-Saharan Africa currently experiences rapidly growing human population, intrinsically tied to substantial changes in land use on shrubland, savanna and mixed woodland ecosystems due to over-exploitation. Significant conversions driving degradation, affecting fire frequency and water availability, and fueling climate change are expected to increase in the immediate future. However, measured data of greenhouse gas emissions as affected by land use change are scarce to entirely lacking from this region. 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. This will be achieved by (1) creation of a network of research clusters (paired sites with natural and altered vegetation) along an aridity gradient in South Africa for ground-based micrometeorological in-situ measurements of energy and matter fluxes, (2) linking biogeochemical functions with ecosystem structure, and eco-physiological properties, (3) description of ecosystem disturbance (and recovery) in terms of ecosystem function such as carbon balance components and water use efficiency, (4) set-up of individual-based models to predict ecosystem dynamics under (post) disturbance managements, (5) combination with long-term landscape dynamic information derived from remote sensing and aerial photography, and (6) development of sustainable management strategies for disturbed ecosystems and land use change. Emphasis is given on validation (by a suite of field measurements) of estimates obtained from eddy covariance, model approaches and satellite derivations.

Estimating surface energy fluxes over an Andalusian Dehesa ecosystem using a thermal-based two-source energy balance model and validation with flux tower measurements

USDA-ARS?s Scientific Manuscript database

The Dehesa, the most widespread agroforestry land-use system in Europe (˜ 3 million ha), is recognized as an example of sustainable land use and for its importance in the rural economy (Diaz et al., 1997; Plieninger and Wilbrand, 2001). It consists of widely-spaced oak forest (mostly Quercus Ilex L....

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.

Soil moisture from ground-based networks and the North American Land Data Assimilation System Phase 2 Model: Are the right values somewhere in between?

NASA Astrophysics Data System (ADS)

Caldwell, T. G.; Scanlon, B. R.; Long, D.; Young, M.

2013-12-01

Soil moisture is the most enigmatic component of the water balance; nonetheless, it is inherently tied to every component of the hydrologic cycle, affecting the partitioning of both water and energy at the land surface. However, our ability to assess soil water storage capacity and status through measurement or modeling is challenged by error and scale. Soil moisture is as difficult to measure as it is to model, yet land surface models and remote sensing products require some means of validation. Here we compare the three major soil moisture monitoring networks across the US, including the USDA Soil Climate Assessment Network (SCAN), NOAA Climate Reference Network (USCRN), and Cosmic Ray Soil Moisture Observing System (COSMOS) to the soil moisture simulated using the North American Land Data Assimilation System (NLDAS) Phase 2. NLDAS runs in near real-time on a 0.125° (12 km) grid over the US, producing ensemble model outputs of surface fluxes and storage. We focus primarily on soil water storage (SWS) in the upper 0-0.1 m zone from the Noah Land Surface Model and secondarily on the effects of error propagation from atmospheric forcing and soil parameterization. No scaling of the observational data was attempted. We simply compared the extracted time series at the nearest grid center from NLDAS and assessed the results by standard model statistics including root mean square error (RMSE) and mean bias estimate (MBE) of the collocated ground station. Observed and modeled data were compared at both hourly and daily mean coordinated universal time steps. In all, ~300 stations were used for 2012. SCAN sites were found to be particularly troublesome at 5- and 10-cm depths. SWS at 163 SCAN sites departed significantly from Noah with a mean R2 of 0.38 × 0.0.23, a mean RMSE of 14.9 mm with a MBE of -13.5 mm. SWS at 111 USCRN sites has a mean R2 of 0.53 × 0.20, a mean RMSE of 8.2 mm with a MBE of -3.7 mm relative to Noah. Finally, 62 COSMOS sites, the instrument with the largest measurement footprint (0.03 km2), we calculated a mean R2 of 0.53 × 0.21, a mean RMSE of 9.7 mm with a MBE of -0.3 mm. Forcing errors and textural misclassifications correlate well with model biases, indicating that scale and structural errors are equally present in NLDAS. Scaling issues aside, these confounding errors make cal/val missions, such as NASA's upcoming Soil Moisture Active Passive (SMAP) mission, problematic without significant quality control and maintenance of for our monitoring networks. Land surface models, such as NLDAS-2, may provide valuable insight into our soil moisture data and somewhere in between the real values likely exist.

Water Resources Investigations at Edwards Air Force Base since 1988

USGS Publications Warehouse

Sneed, Michelle; Nishikawa, Tracy; Martin, Peter

2006-01-01

Edwards Air Force Base (EAFB) in southern California (fig. 1) has relied on ground water to meet its water-supply needs. The extraction of ground water has led to two major problems that can directly affect the mission of EAFB: declining water levels (more than 120 ft since the 1920s) and land subsidence, a gradual downward movement of the land surface (more than 4 ft since the late 1920s). As water levels decline, this valuable resource becomes depleted, thus requiring mitigating measures. Land subsidence has caused cracked (fissured) runways and accelerated erosion on Rogers lakebed. In 1988, the U.S. Geological Survey (USGS), in cooperation with the U.S. Air Force, began investigations of the effects of declining water levels and land subsidence at EAFB and possible mitigation measures, such as the injection of imported surface water into the ground-water system. The cooperative investigations included data collection and analyses, numerical simulations of ground-water flow and land subsidence, and development of a preliminary simulation-optimization model. The results of these investigations indicate that the injection of imported water may help to control land subsidence; however, the potential ground-water-quality impacts are unknown.

The Significance of Land Cover Delineation on Soil Erosion Assessment.

PubMed

Efthimiou, Nikolaos; Psomiadis, Emmanouil

2018-04-25

The study aims to evaluate the significance of land cover delineation on soil erosion assessment. To that end, RUSLE (Revised Universal Soil Loss Equation) was implemented at the Upper Acheloos River catchment, Western Central Greece, annually and multi-annually for the period 1965-92. The model estimates soil erosion as the linear product of six factors (R, K, LS, C, and P) considering the catchment's climatic, pedological, topographic, land cover, and anthropogenic characteristics, respectively. The C factor was estimated using six alternative land use delineations of different resolution, namely the CORINE Land Cover (CLC) project (2000, 2012 versions) (1:100,000), a land use map conducted by the Greek National Agricultural Research Foundation (NAGREF) (1:20,000), a land use map conducted by the Greek Payment and Control Agency for Guidance and Guarantee Community Aid (PCAGGCA) (1:5,000), and the Landsat 8 16-day Normalized Difference Vegetation Index (NDVI) dataset (30 m/pixel) (two approximations) based on remote sensing data (satellite image acquired on 07/09/2016) (1:40,000). Since all other factors remain unchanged per each RUSLE application, the differences among the yielded results are attributed to the C factor (thus the land cover pattern) variations. Validation was made considering the convergence between simulated (modeled) and observed sediment yield. The latter was estimated based on field measurements conducted by the Greek PPC (Public Power Corporation). The model performed best at both time scales using the Landsat 8 (Eq. 13) dataset, characterized by a detailed resolution and a satisfactory categorization, allowing the identification of the most susceptible to erosion areas.

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.

Sensitivity of boundary layer variables to PBL schemes over the central Tibetan Plateau

NASA Astrophysics Data System (ADS)

Xu, L.; Liu, H.; Wang, L.; Du, Q.; Liu, Y.

2017-12-01

Planetary Boundary Layer (PBL) parameterization schemes play critical role in numerical weather prediction and research. They describe physical processes associated with the momentum, heat and humidity exchange between land surface and atmosphere. In this study, two non-local (YSU and ACM2) and two local (MYJ and BouLac) planetary boundary layer parameterization schemes in the Weather Research and Forecasting (WRF) model have been tested over the central Tibetan Plateau regarding of their capability to model boundary layer parameters relevant for surface energy exchange. The model performance has been evaluated against measurements from the Third Tibetan Plateau atmospheric scientific experiment (TIPEX-III). Simulated meteorological parameters and turbulence fluxes have been compared with observations through standard statistical measures. Model results show acceptable behavior, but no particular scheme produces best performance for all locations and parameters. All PBL schemes underestimate near surface air temperatures over the Tibetan Plateau. By investigating the surface energy budget components, the results suggest that downward longwave radiation and sensible heat flux are the main factors causing the lower near surface temperature. Because the downward longwave radiation and sensible heat flux are respectively affected by atmosphere moisture and land-atmosphere coupling, improvements in water vapor distribution and land-atmosphere energy exchange is meaningful for better presentation of PBL physical processes over the central Tibetan Plateau.

Climate and land use changes effects on soil organic carbon stocks in a Mediterranean semi-natural area.

PubMed

Lozano-García, Beatriz; Muñoz-Rojas, Miriam; Parras-Alcántara, Luis

2017-02-01

A thorough knowledge of the effects of climate and land use changes on the soil carbon pool is critical to planning effective strategies for adaptation and mitigation in future scenarios of global climate and land use change. In this study, we used CarboSOIL model to predict changes in soil organic carbon stocks in a semi-natural area of Southern Spain in three different time horizons (2040, 2070, 2100), considering two general circulation models (BCM2 and ECHAM5) and three IPCC scenarios (A1b, A2, B2). The effects of potential land use changes from natural vegetation (Mediterranean evergreen oak woodland) to agricultural land (olive grove and cereal) on soil organic carbon stocks were also evaluated. Predicted values of SOC contents correlated well those measured (R2 ranging from 0.71 at 0-25cm to 0.97 at 50-75cm) showing the efficiency of the model. Results showed substantial differences among time horizons, climate and land use scenarios and soil depth with larger decreases of soil organic carbon stocks in the long term (2100 time horizon) and particularly in olive groves. The combination of climate and land use scenarios (in particular conversion from current 'dehesa' to olive groves) resulted in yet higher losses of soil organic carbon stocks, e.g. -30, -15 and -33% in the 0-25, 25-50 and 50-75cm sections respectively. This study shows the importance of soil organic carbon stocks assessment under both climate and land use scenarios at different soil sections and point towards possible directions for appropriate land use management in Mediterranean semi natural areas. Copyright © 2016 Elsevier B.V. All rights reserved.

The benefits of GIS to land use planning

NASA Astrophysics Data System (ADS)

Strielko, Irina; Pereira, Paulo

2014-05-01

The development of information technologies has significantly changed the approach to land use and spatial planning, management of natural resources. GIS considerably simplifies territorial planning operating analyzing necessary data concerning their spatial relationship that allows carrying out complex assessment of the situation and creates a basis for adoption of more exact and scientifically reasonable decisions in the course of land use. To assess the current land use situation and the possibility of modeling possible future changes associated with complex of adopted measures GIS allows the integration of diverse spatial data, for example, data about soils, climate, vegetation, and other and also to visualize available information in the form of maps, graphs or charts, 3D models. For the purposes of land use GIS allow using data of remote sensing, which allows to make monitoring of anthropogenic influence in a particular area and estimate scales and rates of degradation of green cover, flora and fauna. Assessment of land use can be made in complex or componentwise, indicating the test sites depending on the goals. GIS make it easy to model spatial distribution of various types of pollution of stationary and mobile sources in soil, atmosphere and the hydrological network. Based on results of the analysis made by GIS choose the optimal solutions of land use that provide the minimum impact on environment, make optimal decisions of conflict associated with land use and control of their using. One of the major advantages of using GIS is possibility of the complex analysis in concrete existential aspect. Analytical opportunities of GIS define conditionality of spatial distribution of objects and interrelation communication between them. For a variety of land management objectives analysis method is chosen based on the parameters of the problem and parameters of use of its results.

Unique relation between surface-limited evaporation and relative humidity profiles holds in both field data and climate model simulations

NASA Astrophysics Data System (ADS)

Salvucci, G.; Rigden, A. J.; Gentine, P.; Lintner, B. R.

2013-12-01

A new method was recently proposed for estimating evapotranspiration (ET) from weather station data without requiring measurements of surface limiting factors (e.g. soil moisture, leaf area, canopy conductance) [Salvucci and Gentine, 2013, PNAS, 110(16): 6287-6291]. Required measurements include diurnal air temperature, specific humidity, wind speed, net shortwave radiation, and either measured or estimated incoming longwave radiation and ground heat flux. The approach is built around the idea that the key, rate-limiting, parameter of typical ET models, the land-surface resistance to water vapor transport, can be estimated from an emergent relationship between the diurnal cycle of the relative humidity profile and ET. The emergent relation is that the vertical variance of the relative humidity profile is less than what would occur for increased or decreased evaporation rates, suggesting that land-atmosphere feedback processes minimize this variance. This relation was found to hold over a wide range of climate conditions (arid to humid) and limiting factors (soil moisture, leaf area, energy) at a set of Ameriflux field sites. While the field tests in Salvucci and Gentine (2013) supported the minimum variance hypothesis, the analysis did not reveal the mechanisms responsible for the behavior. Instead the paper suggested, heuristically, that the results were due to an equilibration of the relative humidity between the land surface and the surface layer of the boundary layer. Here we apply this method using surface meteorological fields simulated by a global climate model (GCM), and compare the predicted ET to that simulated by the climate model. Similar to the field tests, the GCM simulated ET is in agreement with that predicted by minimizing the profile relative humidity variance. A reasonable interpretation of these results is that the feedbacks responsible for the minimization of the profile relative humidity variance in nature are represented in the climate model. The climate model components, in particular the land surface model and boundary layer representation, can thus be analyzed in controlled numerical experiments to discern the specific processes leading to the observed behavior. Results of this analysis will be presented.

Estimation of Chinese surface NO2 concentrations combining satellite data and Land Use Regression

NASA Astrophysics Data System (ADS)

Anand, J.; Monks, P.

2016-12-01

Monitoring surface-level air quality is often limited by in-situ instrument placement and issues arising from harmonisation over long timescales. Satellite instruments can offer a synoptic view of regional pollution sources, but in many cases only a total or tropospheric column can be measured. In this work a new technique of estimating surface NO2 combining both satellite and in-situ data is presented, in which a Land Use Regression (LUR) model is used to create high resolution pollution maps based on known predictor variables such as population density, road networks, and land cover. By employing a mixed effects approach, it is possible to take advantage of the spatiotemporal variability in the satellite-derived column densities to account for daily and regional variations in surface NO2 caused by factors such as temperature, elevation, and wind advection. In this work, surface NO2 maps are modelled over the North China Plain and Pearl River Delta during high-pollution episodes by combining in-situ measurements and tropospheric columns from the Ozone Monitoring Instrument (OMI). The modelled concentrations show good agreement with in-situ data and surface NO2 concentrations derived from the MACC-II global reanalysis.

Vertical motions in Northern Victoria Land inferred from GPS: A comparison with a glacial isostatic adjustment model

USGS Publications Warehouse

Mancini, F.; Negusini, M.; Zanutta, A.; Capra, A.

2007-01-01

Following the densification of GPS permanent and episodic trackers in Antarctica, geodetic observations are playing an increasing role in geodynamics research and the study of the glacial isostatic adjustment (GIA). The improvement in geodetic measurements accuracy suggests their use in constraining GIA models. It is essential to have a deeper knowledge on the sensitivity of GPS data to motionsrelated to long-term ice mass changes and the present-day mass imbalance of the ice sheets. In order to investigate the geodynamic phenomena in Northern Victoria Land (NVL), GPS geodetic observations were made during the last decade within the VLNDEF (Victoria Land Network for Deformation control) project. The processed data provided a picture of the motions occurring in NVL with a high level of accuracy and depicts, for the whole period, a well defined pattern of vertical motion. The comparison between GPS-derived vertical displacementsand GIA is addressed, showing a good degree of agreement and highlighting the future use of geodetic GPS measurements as constraints in GIA models. In spite of this agreement, the sensitivity of GPS vertical rates to non-GIA vertical motions has to be carefully evaluated.

Bridging the GAPS from Space: A Research/Educational Partnership in the Upper Delaware River Basin

NASA Astrophysics Data System (ADS)

Brown de Colstoun, E.; Robin, J.; Minelli, S.; Katsaros, M.; Peterec, I.; Sandt, K.

2006-05-01

The National Park Service (NPS) Inventory and Monitoring (I&M) Program is currently developing scientific protocols to inventory and monitor the natural resources of 270 park units at the national level. These are aimed at providing critical tools needed by park managers for effective decision-making regarding the management and stewardship of the resources they are charged with protecting. We are currently developing a satellite-based regional land cover and land use monitoring protocol that addresses the immediate needs of the NPS I&M. This is a pilot project that examines land cover/use changes in and around the Upper Delaware Scenic and Recreational River and Delaware Water Gap National Recreation Area national parks from Landsat data for the period 1984 to 2005, in one the fastest growing regions in the country. The products resulting from the application of the protocols are then used to guide the simulation of land cover/use changes within a simple Soil-Vegetation-Atmosphere-Transfer (SVAT) model called GAPS in order to better understand the consequences of the measured land cover/use change on the water and energy cycles of the parks and surrounding areas. The data needed for product validation and model parameterization are being acquired with the assistance of students and educators from area schools using protocols established through the GLOBE program. Through focused workshops organized in collaboration with NPS educational specialists and PA regional educational service agencies called Intermediate Units, and participation in hands-on field measurement campaigns, students and educators are learning about satellite remote sensing interpretation, land cover classification, and how to measure/monitor changes in land cover/use in their communities. Students will also assist in the model simulations using the data they acquire in the field. This partnership between the Principal Investigator, the NPS, Intermediate Units and area students and educators is one that clearly benefits the development and validation of the research but also provides the compelling story line for a variety of educational activities, all within the spectacular setting of our National Parks. We are building here on existing relationships between NASA, the NPS, and local governments and schools to strengthen the local curriculum in the natural sciences and to enhance the study and appreciation of the Earth as a system of interconnected parts.

Simulations of the general circulation of the Martian atmosphere. II - Seasonal pressure variations

NASA Technical Reports Server (NTRS)

Pollack, James B.; Haberle, Robert M.; Murphy, James R.; Schaeffer, James; Lee, Hilda

1993-01-01

The CO2 seasonal cycle of the Martian atmosphere and surface is simulated with a hybrid energy balance model that incorporates dynamical and radiation information from a large number of general circulation model runs. This information includes: heating due to atmospheric heat advection, the seasonally varying ratio of the surface pressure at the two Viking landing sites to the globally averaged pressure, the rate of CO2 condensation in the atmosphere, and solar heating of the atmosphere and surface. The predictions of the energy balance model are compared with the seasonal pressure variations measured at the two Viking landing sites and the springtime retreat of the seasonal polar cap boundaries. The following quantities are found to have a strong influence on the seasonal pressures at the Viking landing sites: albedo of the seasonal CO2 ice deposits, emissivity of this deposit, atmospheric heat advection, and the pressure ratio.

The influence of grazing on land surface climatological variables

NASA Technical Reports Server (NTRS)

Seastedt, T. R.; Dyer, M. I.

1988-01-01

Research accomplishments in empirical measurements, laboratory analyses, data analyses, and modeling are summarized. Publications are listed. Presentations made during the funding period are also listed.

Integrated modelling of nitrate loads to coastal waters and land rent applied to catchment-scale water management.

PubMed

Refsgaard, A; Jacobsen, T; Jacobsen, B; Ørum, J-E

2007-01-01

The EU Water Framework Directive (WFD) requires an integrated approach to river basin management in order to meet environmental and ecological objectives. This paper presents concepts and full-scale application of an integrated modelling framework. The Ringkoebing Fjord basin is characterized by intensive agricultural production and leakage of nitrate constitute a major pollution problem with respect groundwater aquifers (drinking water), fresh surface water systems (water quality of lakes) and coastal receiving waters (eutrophication). The case study presented illustrates an advanced modelling approach applied in river basin management. Point sources (e.g. sewage treatment plant discharges) and distributed diffuse sources (nitrate leakage) are included to provide a modelling tool capable of simulating pollution transport from source to recipient to analyse the effects of specific, localized basin water management plans. The paper also includes a land rent modelling approach which can be used to choose the most cost-effective measures and the location of these measures. As a forerunner to the use of basin-scale models in WFD basin water management plans this project demonstrates the potential and limitations of comprehensive, integrated modelling tools.

Impact of snow gliding on soil redistribution for a sub-alpine area in Switzerland

NASA Astrophysics Data System (ADS)

Meusburger, K.; Leitinger, G.; Mabit, L.; Mueller, M. H.; Alewell, C.

2013-07-01

The aim of this study is to assess the importance of snow gliding as soil erosion agent for four different land use/land cover types in a sub-alpine area in Switzerland. The 14 investigated sites are located close to the valley bottom at approximately 1500 m a.s.l., while the elevation of the surrounding mountain ranges is about 2500 m a.s.l. We used two different approaches to estimate soil erosion rates: the fallout radionuclide 137Cs and the Revised Universal Soil Loss Equation (RUSLE). The RUSLE model is suitable to estimate soil loss by water erosion, while the 137Cs method integrates soil loss due to all erosion agents involved. Thus, we hypothesise that the soil erosion rates determined with the 137Cs method are higher and that the observed discrepancy between the erosion rate of RUSLE and the 137Cs method is related to snow gliding. Cumulative snow glide distance was measured for the sites in the winter 2009/2010 and modelled for the surrounding area with the Spatial Snow Glide Model (SSGM). Measured snow glide distance range from 0 to 189 cm with lower values for the north exposed slopes. We observed a reduction of snow glide distance with increasing surface roughness of the vegetation, which is an important information with respect to conservation planning and expected land use changes in the Alps. Our hypothesis was confirmed, the difference of RUSLE and 137Cs erosion rates was correlated to the measured snow glide distance (R2 = 0.73; p < 0.005). A high difference (lower proportion of water erosion compared to total net erosion) was observed for high snow glide rates and vice versa. The SSGM reproduced the relative difference of the measured snow glide values between different land use/land cover types. The resulting map highlights the relevance of snow gliding for large parts of the investigated area. Based on these results, we conclude that snow gliding is a key process impacting soil erosion pattern and magnitude in sub-alpine areas with similar topographic and climatic conditions.

Regional Climate Modeling and Remote Sensing to Characterize Impacts of Civil War Driven Land Use Change on Regional Hydrology and Climate

NASA Astrophysics Data System (ADS)

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

2016-12-01

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 extensive enough. 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. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from an extended civil conflict in Mozambique. Civil war from 1977-1992 in Mozambique led to land use change at a regional scale as a result of the collapse of large herbivore populations due to poaching. Since the war ended, farming has increased, poaching was curtailed, and animal populations were reintroduced. In this study LULC in a region encompassing Gorongosa is classified at three instances between 1977 to 2015 using Landsat imagery. 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 conflict-driven land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the civil war. Analysis of the Landsat data shows measurable land cover change from 1977-present as tree cover encroached into grasslands. Initial tests show corresponding sensitivities to different LULC schemes within the WRF model. Preliminary results suggest that the war did indeed impact regional hydroclimate in a significant way via its direct and indirect impacts on land-atmosphere interactions. Results of this study suggest that LULC change arising from regional conflicts are a potentially understudied, yet important human process to capture in both regional reanalyses and climate change projections.

Enhancing Global Land Surface Hydrology Estimates from the NASA MERRA Reanalysis Using Precipitation Observations and Model Parameter Adjustments

NASA Technical Reports Server (NTRS)

Reichle, Rolf; Koster, Randal; DeLannoy, Gabrielle; Forman, Barton; Liu, Qing; Mahanama, Sarith; Toure, Ally

2011-01-01

The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides. in addition to atmospheric fields. global estimates of soil moisture, latent heat flux. snow. and runoff for J 979-present. This study introduces a supplemental and improved set of land surface hydrological fields ('MERRA-Land') generated by replaying a revised version of the land component of the MERRA system. Specifically. the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameters in the rainfall interception model, changes that effectively correct for known limitations in the MERRA land surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim reanalysis. MERRA-Land and ERA-Interim root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 15 basins in the western US) of MERRA and MERRA-Land is typically higher than that of ERA-Interim. With a few exceptions. the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using '\\-tERRA output for land surface hydrological studies.

A hydrologic network supporting spatially referenced regression modeling in the Chesapeake Bay watershed

USGS Publications Warehouse

Brakebill, J.W.; Preston, S.D.

2003-01-01

The U.S. Geological Survey has developed a methodology for statistically relating nutrient sources and land-surface characteristics to nutrient loads of streams. The methodology is referred to as SPAtially Referenced Regressions On Watershed attributes (SPARROW), and relates measured stream nutrient loads to nutrient sources using nonlinear statistical regression models. A spatially detailed digital hydrologic network of stream reaches, stream-reach characteristics such as mean streamflow, water velocity, reach length, and travel time, and their associated watersheds supports the regression models. This network serves as the primary framework for spatially referencing potential nutrient source information such as atmospheric deposition, septic systems, point-sources, land use, land cover, and agricultural sources and land-surface characteristics such as land use, land cover, average-annual precipitation and temperature, slope, and soil permeability. In the Chesapeake Bay watershed that covers parts of Delaware, Maryland, Pennsylvania, New York, Virginia, West Virginia, and Washington D.C., SPARROW was used to generate models estimating loads of total nitrogen and total phosphorus representing 1987 and 1992 land-surface conditions. The 1987 models used a hydrologic network derived from an enhanced version of the U.S. Environmental Protection Agency's digital River Reach File, and course resolution Digital Elevation Models (DEMs). A new hydrologic network was created to support the 1992 models by generating stream reaches representing surface-water pathways defined by flow direction and flow accumulation algorithms from higher resolution DEMs. On a reach-by-reach basis, stream reach characteristics essential to the modeling were transferred to the newly generated pathways or reaches from the enhanced River Reach File used to support the 1987 models. To complete the new network, watersheds for each reach were generated using the direction of surface-water flow derived from the DEMs. This network improves upon existing digital stream data by increasing the level of spatial detail and providing consistency between the reach locations and topography. The hydrologic network also aids in illustrating the spatial patterns of predicted nutrient loads and sources contributed locally to each stream, and the percentages of nutrient load that reach Chesapeake Bay.

Human Land-Use Practices Lead to Global Long-Term Increases in Photosynthetic Capacity

NASA Technical Reports Server (NTRS)

Mueller, Thomas; Tucker, Compton J.; Dressler, Gunnar; Pinzon, Jorge E.; Leimgruber, Peter; Dubayah, Ralph O.; Hurtt, George C.; Boehning-Gaese, Katrin; Fagan, William F.

2014-01-01

Long-term trends in photosynthetic capacity measured with the satellite-derived Normalized Difference Vegetation Index (NDVI) are usually associated with climate change. Human impacts on the global land surface are typically not accounted for. Here, we provide the first global analysis quantifying the effect of the earth's human footprint on NDVI trends. Globally, more than 20% of the variability in NDVI trends was explained by anthropogenic factors such as land use, nitrogen fertilization, and irrigation. Intensely used land classes, such as villages, showed the greatest rates of increase in NDVI, more than twice than those of forests. These findings reveal that factors beyond climate influence global long-term trends in NDVI and suggest that global climate change models and analyses of primary productivity should incorporate land use effects.

Reestablishing Public Health and Land Use Planning to Protect Public Water Supplies

PubMed Central

Greenberg, Michael; Mayer, Henry; Miller, K. Tyler; Hordon, Robert; Knee, Daniel

2003-01-01

Objectives. This study measured the extent to which land use, design, and engineering practices could reduce contamination of major public water supplies. Methods. Key parcels of land were identified in New Jersey, and the potential uncontrolled loading of contaminants was estimated with the US Environmental Protection Agency’s Long-Term Hydrologic Impact Assessment model for a variety of land use, design, and engineering scenarios. Results. High-density per-acre development and engineering controls, along with housing and light commercial activity near main railroads, would substantially reduce runoff. Conclusions. In New Jersey, government and purveyor action is being taken as a result of, and in support of, these findings. PMID:12948974

The role of land use/land cover dependent preferential flow paths in hydrologic response of steep and seasonal tropical catchments

NASA Astrophysics Data System (ADS)

Cheng, Y.; Ogden, F. L.; Zhu, J.

2017-12-01

The hydrologic behavior of steep catchments with saprolitic soils in the humid seasonal tropics varies with land use and cover, even when they have identical topographic index and slope distributions, underlying geology and soils textures. Forested catchments can produce more baseflow during the dry season compared to catchments containing substantial amount of pasture, the so-called "sponge effect". During rainfall events, forested catchments can also exhibit lower peak runoff rates and runoff efficiencies compared to pasture catchments. We hypothesize that hydrologic effects of land use arise from differences in preferential flow paths (PFPs) formed by biotic and abiotic factors in the upper one to two meters of soil and that land use effects on hydrological response are described by the relative amounts of forest and pasture within a catchment. Furthermore, we hypothesize that infiltration measurements at different scales allow estimation of PFP-related parameters. These hypotheses are tested by a model that explicitly simulates PFPs using distinct input parameter sets for forest and pasture. Runoff observations from three catchments with pasture, forest, and a mosaic of subsistence agricultural land covers allow model evaluation. Multiple objective criteria indicate that field measurements of infiltration enable PFP-relevant parameter identification and that pasture and forest end member parameter sets describe much of the observed difference. Analysis of water balance components and comparison between average transient water table depth and vertical PFP flow capacity demonstrate that the interplay of lateral and vertical PFPs contribute to the sponge-effect and can explain differences in peak runoff and runoff efficiency.

Increased Fidelity in Prediction Methods For Landing Gear Noise

NASA Technical Reports Server (NTRS)

Lopes, Leonard V.; Brentner, Kenneth S.; Morris, Philip J.; Lockard, David P.

2006-01-01

An aeroacoustic prediction scheme has been developed for landing gear noise. The method is designed to handle the complex landing gear geometry of current and future aircraft. The gear is represented by a collection of subassemblies and simple components that are modeled using acoustic elements. These acoustic elements are generic, but generate noise representative of the physical components on a landing gear. The method sums the noise radiation from each component of the undercarriage in isolation accounting for interference with adjacent components through an estimate of the local upstream and downstream flows and turbulence intensities. The acoustic calculations are made in the code LGMAP, which computes the sound pressure levels at various observer locations. The method can calculate the noise from the undercarriage in isolation or installed on an aircraft for both main and nose landing gear. Comparisons with wind tunnel and flight data are used to initially calibrate the method, then it may be used to predict the noise of any landing gear. In this paper, noise predictions are compared with wind tunnel data for model landing gears of various scales and levels of fidelity, as well as with flight data on fullscale undercarriages. The present agreement between the calculations and measurements suggests the method has promise for future application in the prediction of airframe noise.

Assessment of changes in nutrient and sediment delivery to and carbon accumulation in coastal oceans of the Eastern United States

NASA Astrophysics Data System (ADS)

Bergamaschi, B. A.; Smith, R. A.; Shih, J. S.; Sohl, T. L.; Sleeter, B. M.; Zhu, Z.

2014-12-01

Land-use and land-cover distributions are primary determinants of terrestrial fluxes of sediments and nutrients to coastal oceans. Sediment and nutrient delivery to coastal waters have already been significantly altered by changes in population and land use, resulting in modified patterns of coastal production and carbon storage. Continued population growth and increasing agricultural areal extent and intensity are expected to accelerate these changes. The USGS LandCarbon project developed prospective future land use and land cover projections based on IPCC scenarios A1b, A2 and B1 to 2050 as the basis for a multitude of biogeochemical assessments. We assessed the impacts on delivery of nutrients and sediments to the coastal ocean, and concomitant carbon storage. Fluxes were estimated using the SPARROW model, calibrated on historical water quality measurements. Significantly greater fluxes of nutrients and sediments to coastal waters by 2050 are projected by the model. For example, for the Eastern United States, nitrate fluxes for 2050 are projected to be16 to 52 percent higher than the baseline year, depending on scenario. As a consequence, an associated increase in the frequency and duration of coastal and estuarine hypoxia events and harmful algal blooms could be expected. Model estimates indicate that these prospective future nutrient and sediment fluxes will increase carbon storage rates in coastal waters by 18 to 56 percent in some regions.

Impacts of land use changes on net ecosystem production in the Taihu Lake Basin of China from 1985 to 2010

NASA Astrophysics Data System (ADS)

Xu, Xibao; Yang, Guishan; Tan, Yan; Tang, Xuguang; Jiang, Hong; Sun, Xiaoxiang; Zhuang, Qianlai; Li, Hengpeng

2017-03-01

Land use changes play a major role in determining sources and sinks of carbon at regional and global scales. This study employs a modified Global biome model-biogeochemical cycle model to examine the changes in the spatiotemporal pattern of net ecosystem production (NEP) in the Taihu Lake Basin of China during 1985-2010 and the extent to which land use change impacted NEP. The model is calibrated with observed NEP at three flux sites for three dominant land use types in the basin including cropland, evergreen needleleaf forest, and mixed forest. Two simulations are conducted to distinguish the net effects of land use change and increasing atmospheric concentrations of CO2 and nitrogen deposition on NEP. The study estimates that NEP in the basin decreased by 9.8% (1.57 Tg C) from 1985 to 2010, showing an overall downward trend. The NEP distribution exhibits an apparent spatial heterogeneity at the municipal level. Land use changes during 1985-2010 reduced the regional NEP (3.21 Tg C in year 2010) by 19.9% compared to its 1985 level, while the increasing atmospheric CO2 concentrations and nitrogen deposition compensated for a half of the total carbon loss. Critical measures for regulating rapid urban expansion and population growth and reinforcing environment protection programs are recommended to increase the regional carbon sink.

GLEAM version 3: Global Land Evaporation Datasets and Model

NASA Astrophysics Data System (ADS)

Martens, B.; Miralles, D. G.; Lievens, H.; van der Schalie, R.; de Jeu, R.; Fernandez-Prieto, D.; Verhoest, N.

2015-12-01

Terrestrial evaporation links energy, water and carbon cycles over land and is therefore a key variable of the climate system. However, the global-scale magnitude and variability of the flux, and the sensitivity of the underlying physical process to changes in environmental factors, are still poorly understood due to limitations in in situ measurements. As a result, several methods have risen to estimate global patterns of land evaporation from satellite observations. However, these algorithms generally differ in their approach to model evaporation, resulting in large differences in their estimates. One of these methods is GLEAM, the Global Land Evaporation: the Amsterdam Methodology. GLEAM estimates terrestrial evaporation based on daily satellite observations of meteorological variables, vegetation characteristics and soil moisture. Since the publication of the first version of the algorithm (2011), the model has been widely applied to analyse trends in the water cycle and land-atmospheric feedbacks during extreme hydrometeorological events. A third version of the GLEAM global datasets is foreseen by the end of 2015. Given the relevance of having a continuous and reliable record of global-scale evaporation estimates for climate and hydrological research, the establishment of an online data portal to host these data to the public is also foreseen. In this new release of the GLEAM datasets, different components of the model have been updated, with the most significant change being the revision of the data assimilation algorithm. In this presentation, we will highlight the most important changes of the methodology and present three new GLEAM datasets and their validation against in situ observations and an alternative dataset of terrestrial evaporation (ERA-Land). Results of the validation exercise indicate that the magnitude and the spatiotemporal variability of the modelled evaporation agree reasonably well with the estimates of ERA-Land and the in situ observations. It is also shown that the performance of the revised model is higher compared to the original one.

Using NASA Earth Observing Satellites and Statistical Model Analysis to Monitor Vegetation and Habitat Rehabilitation in Southwest Virginia's Reclaimed Mine Lands

NASA Astrophysics Data System (ADS)

Tate, Z.; Dusenge, D.; Elliot, T. S.; Hafashimana, P.; Medley, S.; Porter, R. P.; Rajappan, R.; Rodriguez, P.; Spangler, J.; Swaminathan, R. S.; VanGundy, R. D.

2014-12-01

The majority of the population in southwest Virginia depends economically on coal mining. In 2011, coal mining generated $2,000,000 in tax revenue to Wise County alone. However, surface mining completely removes land cover and leaves the land exposed to erosion. The destruction of the forest cover directly impacts local species, as some are displaced and others perish in the mining process. Even though surface mining has a negative impact on the environment, land reclamation efforts are in place to either restore mined areas to their natural vegetated state or to transform these areas for economic purposes. This project aimed to monitor the progress of land reclamation and the effect on the return of local species. By incorporating NASA Earth observations, such as Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM), re-vegetation process in reclamation sites was estimated through a Time series analysis using the Normalized Difference Vegetation Index (NDVI). A continuous source of cloud free images was accomplished by utilizing the Spatial and Temporal Adaptive Reflectance Fusion Model (STAR-FM). This model developed synthetic Landsat imagery by integrating the high-frequency temporal information from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and high-resolution spatial information from Landsat sensors In addition, the Maximum Entropy Modeling (MaxENT), an eco-niche model was used to estimate the adaptation of animal species to the newly formed habitats. By combining factors such as land type, precipitation from Tropical Rainfall Measuring Mission (TRMM), and slope from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the MaxENT model produced a statistical analysis on the probability of species habitat. Altogether, the project compiled the ecological information which can be used to identify suitable habitats for local species in reclaimed mined areas.

Large-scale experimental technology with remote sensing in land surface hydrology and meteorology

NASA Technical Reports Server (NTRS)

Brutsaert, Wilfried; Schmugge, Thomas J.; Sellers, Piers J.; Hall, Forrest G.

1988-01-01

Two field experiments to study atmospheric and land surface processes and their interactions are summarized. The Hydrologic-Atmospheric Pilot Experiment, which tested techniques for measuring evaporation, soil moisture storage, and runoff at scales of about 100 km, was conducted over a 100 X 100 km area in France from mid-1985 to early 1987. The first International Satellite Land Surface Climatology Program field experiment was conducted in 1987 to develop and use relationships between current satellite measurements and hydrologic, climatic, and biophysical variables at the earth's surface and to validate these relationships with ground truth. This experiment also validated surface parameterization methods for simulation models that describe surface processes from the scale of vegetation leaves up to scales appropriate to satellite remote sensing.

Switchgrass leaf area index and light extinction coefficients

USDA-ARS?s Scientific Manuscript database

Biomass production simulation modeling for plant species is often dependent upon accurate simulation or measurement of canopy light interception and radiation use efficiency. With the recent interest in converting large tracts of land to biofuel species cropping, modeling vegetative yield with grea...

Observations of land-atmosphere interactions using satellite data

NASA Astrophysics Data System (ADS)

Green, Julia; Gentine, Pierre; Konings, Alexandra; Alemohammad, Hamed; Kolassa, Jana

2016-04-01

Observations of land-atmosphere interactions using satellite data Julia Green (1), Pierre Gentine (1), Alexandra Konings (1,2), Seyed Hamed Alemohammad (3), Jana Kolassa (4) (1) Columbia University, Earth and Environmental Engineering, NY, NY, USA, (2) Stanford University, Environmental Earth System Science, Stanford, CA, USA, (3) Massachusetts Institute of Technology, Civil and Environmental Engineering, Cambridge, MA, USA, (4) National Aeronautics and Space Administration/Goddard Space Flight Center, Greenbelt, MD, USA. Previous studies of global land-atmosphere hotspots have often relied solely on data from global models with the consequence that they are sensitive to model error. On the other hand, by only analyzing observations, it can be difficult to distinguish causality from mere correlation. In this study, we present a general framework for investigating land-atmosphere interactions using Granger Causality analysis applied to remote sensing data. Based on the near linear relationship between chlorophyll sun induced fluorescence (SIF) and photosynthesis (and thus its relationship with transpiration), we use the GOME-2 fluorescence direct measurements to quantify the surface fluxes between the land and atmosphere. By using SIF data to represent the flux, we bypass the need to use soil moisture data from FLUXNET (limited spatially and temporally) or remote sensing (limited by spatial resolution, canopy interference, measurement depth, and radio frequency interference) thus eliminating additional uncertainty. The Granger Causality analysis allows for the determination of the strength of the two-way causal relationship between SIF and several climatic variables: precipitation, radiation and temperature. We determine that warm regions transitioning from water to energy limitation exhibit strong feedbacks between the land surface and atmosphere due to their high sensitivity to climate and weather variability. Tropical rainforest regions show low magnitudes of causal feedback likely due to other factors influencing the land surface such as phenological controls (e.g. leaf area index), nutrient limitations or soil texture. These results were then compared to CMIP5 GCM results using GPP in place of SIF. GCM results varied greatly between models as well as with the observational data analysis indicating deficiencies in the representation of certain modeled phenomena such as low level clouds and boundary layer development. This study highlights the need for GCM improvement to more accurately capture the feedbacks between the land and atmosphere. These results have the potential to improve our understanding of the underlying mechanisms between land and atmosphere coupling, which could ultimately be used to improve weather and climate predictions.

Consequences of kriging and land use regression for PM2.5 predictions in epidemiologic analyses: Insights into spatial variability using high-resolution satellite data

PubMed Central

Alexeeff, Stacey E.; Schwartz, Joel; Kloog, Itai; Chudnovsky, Alexandra; Koutrakis, Petros; Coull, Brent A.

2016-01-01

Many epidemiological studies use predicted air pollution exposures as surrogates for true air pollution levels. These predicted exposures contain exposure measurement error, yet simulation studies have typically found negligible bias in resulting health effect estimates. However, previous studies typically assumed a statistical spatial model for air pollution exposure, which may be oversimplified. We address this shortcoming by assuming a realistic, complex exposure surface derived from fine-scale (1km x 1km) remote-sensing satellite data. Using simulation, we evaluate the accuracy of epidemiological health effect estimates in linear and logistic regression when using spatial air pollution predictions from kriging and land use regression models. We examined chronic (long-term) and acute (short-term) exposure to air pollution. Results varied substantially across different scenarios. Exposure models with low out-of-sample R2 yielded severe biases in the health effect estimates of some models, ranging from 60% upward bias to 70% downward bias. One land use regression exposure model with greater than 0.9 out-of-sample R2 yielded upward biases up to 13% for acute health effect estimates. Almost all models drastically underestimated the standard errors. Land use regression models performed better in chronic effects simulations. These results can help researchers when interpreting health effect estimates in these types of studies. PMID:24896768

Improving the Fit of a Land-Surface Model to Data Using its Adjoint

NASA Astrophysics Data System (ADS)

Raoult, Nina; Jupp, Tim; Cox, Peter; Luke, Catherine

2016-04-01

Land-surface models (LSMs) are crucial components of the Earth System Models (ESMs) which are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. In this study, JULES is automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. We present an introduction to the adJULES system and demonstrate its ability to improve the model-data fit using eddy covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the 5 Plant Functional Types (PFTS) in JULES. The optimised PFT-specific parameters improve the performance of JULES over 90% of the FLUXNET sites used in the study. These reductions in error are shown and compared to reductions found due to site-specific optimisations. Finally, we show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.

Evaluating the Assumptions of Surface Reflectance and Aerosol Type Selection Within the MODIS Aerosol Retrieval Over Land: The Problem of Dust Type Selection

NASA Technical Reports Server (NTRS)

Mielonen, T.; Levy, R. C.; Aaltonen, V.; Komppula, M.; de Leeuw, G.; Huttunen, J.; Lihavainen, H.; Kolmonen, P.; Lehtinen, K. E. J.; Arola, A.

2011-01-01

Aerosol Optical Depth (AOD) and Angstrom exponent (AE) values derived with the MODIS retrieval algorithm over land (Collection 5) are compared with ground based sun photometer measurements at eleven sites spanning the globe. Although, in general, total AOD compares well at these sites (R2 values generally over 0.8), there are cases (from 2 to 67% of the measurements depending on the site) where MODIS clearly retrieves the wrong spectral dependence, and hence, an unrealistic AE value. Some of these poor AE retrievals are due to the aerosol signal being too small (total AOD<0.3) but in other cases the AOD should have been high enough to derive accurate AE. However, in these cases, MODIS indicates AE values close to 0.6 and zero fine model weighting (FMW), i.e. dust model provides the best fitting to the MODIS observed reflectance. Yet, according to evidence from the collocated sun photometer measurements and back-trajectory analyses, there should be no dust present. This indicates that the assumptions about aerosol model and surface properties made by the MODIS algorithm may have been incorrect. Here we focus on problems related to parameterization of the land-surface optical properties in the algorithm, in particular the relationship between the surface reflectance at 660 and 2130 nm.

Aeroacoustic Study of a High-Fidelity Aircraft Model. Part 2; Unsteady Surface Pressures

NASA Technical Reports Server (NTRS)

Khorrami, Mehdi R.; Neuhart, Danny H.

2012-01-01

In this paper, we present unsteady surface pressure measurements for an 18%-scale, semi-span Gulfstream aircraft model. This high-fidelity model is being used to perform detailed studies of airframe noise associated with main landing gear, flap components, and gear-flap interaction noise, as well as to evaluate novel noise reduction concepts. The aerodynamic segment of the tests, conducted in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel, was completed in November 2010. To discern the characteristics of the surface pressure fluctuations in the vicinity of the prominent noise sources, unsteady sensors were installed on the inboard and outboard flap edges, and on the main gear wheels, struts, and door. Various configurations were tested, including flap deflections of 0?, 20?, and 39?, with and without the main landing gear. The majority of unsteady surface pressure measurements were acquired for the nominal landing configuration where the main gear was deployed and the flap was deflected 39?. To assess the Mach number variation of the surface pressure amplitudes, measurements were obtained at Mach numbers of 0.16, 0.20, and 0.24. Comparison of the unsteady surface pressures with the main gear on and off shows significant interaction between the gear wake and the inboard flap edge, resulting in higher amplitude fluctuations when the gear is present.

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

Urban surface energy fluxes based on remotely-sensed data and micrometeorological measurements over the Kansai area, Japan

NASA Astrophysics Data System (ADS)

Sukeyasu, T.; Ueyama, M.; Ando, T.; Kosugi, Y.; Kominami, Y.

2017-12-01

The urban heat island is associated with land cover changes and increases in anthropogenic heat fluxes. Clear understanding of the surface energy budget at urban area is the most important for evaluating the urban heat island. In this study, we develop a model based on remotely-sensed data for the Kansai area in Japan and clarify temporal transitions and spatial distributions of the surface energy flux from 2000 to 2016. The model calculated the surface energy fluxes based on various satellite and GIS products. The model used land surface temperature, surface emissivity, air temperature, albedo, downward shortwave radiation and land cover/use type from the moderate resolution imaging spectroradiometer (MODIS) under cloud free skies from 2000 to 2016 over the Kansai area in Japan (34 to 35 ° N, 135 to 136 ° E). Net radiation was estimated by a radiation budget of upward/downward shortwave and longwave radiation. Sensible heat flux was estimated by a bulk aerodynamic method. Anthropogenic heat flux was estimated by the inventory data. Latent heat flux was examined with residues of the energy budget and parameterization of bulk transfer coefficients. We validated the model using observed fluxes from five eddy-covariance measurement sites: three urban sites and two forested sites. The estimated net radiation roughly agreed with the observations, but the sensible heat flux were underestimated. Based on the modeled spatial distributions of the fluxes, the daytime net radiation in the forested area was larger than those in the urban area, owing to higher albedo and land surface temperatures in the urban area than the forested area. The estimated anthropogenic heat flux was high in the summer and winter periods due to increases in energy-requirements.

Quantifying the impacts of land use change on soil organic carbon losses in tropical peatlands

NASA Astrophysics Data System (ADS)

Farmer, J.; Smith, J.; Smith, P.; Matthews, R.

2012-04-01

The challenge of collecting field measurements of soil carbon dioxide (CO2) efflux and soil carbon (C) in tropical peatlands creates an opportunity for the use of SOC models for predicting local and regional impacts of land use and climate change on these soils, offering a way of translating this limited data into tangible results. Previously, no soil C model existed for use in non-steady state sites such as those found on tropical peats- in particular peat swamp forests which accumulate C, and oil palm plantations which are grown for 20-25 years between re-plantings. A simple, user friendly model has been created for use by scientists, policy makers and plantation managers. This model uses only limited inputs to predict the changes to soil C from land use and climate change. The model runs on the assumption that plant inputs can be related to yield, and that this can be used to derive the decomposition of SOM. It uses a simple decomposition response to determine the changes to the soil C. The model can run in a basic form if data is very limited, or a more complex form with modifiers for temperature, pH, salinity and soil moisture if this data is available. Using measured CO2 efflux and soil C values from peat cores, combined with literature values, we demonstrate the efficacy of the model, showing how we have identified and addressed some of the issues related to modelling soil C losses from tropical peat soils under land use change. Key challenges addressed included quantifying the effects of drainage when peat swamp forests are converted to oil palm plantations, and comparing field results between sites because in oil palm plantations the original soil conditions prior to conversion from peat swamp forest were largely unknown.

Advances in wind erosion modelling in Europe

NASA Astrophysics Data System (ADS)

Borrelli, Pasquale; Lugato, Emanuele; Alewell, Christine; Montanarella, Luca; Panagos, Panos

2017-04-01

Soil erosion by wind is a serious environmental problem often resulting in severe forms of soil degradation. Wind erosion is also a phenomenon relevant for Europe, although this land degradation process has been overlooked until very recently. The state-of-the-art literature presents wind erosion as a process that locally affects the semi-arid areas of the Mediterranean region as well as the temperate climate areas of the northern European countries. Actual observations, field measurements and modelling assessments, however, are all extremely limited and highly unequally distributed across Europe. As a result, we currently lack comprehensive understanding about where and when wind erosion occurs in Europe, and the intensity of erosion that poses a threat to agricultural productivity. Today's challenge is to integrate the insights of local experiments and field-scale models into a new generation of large-scale wind erosion models. While naturally being less accurate than field-scale models, these large-scale modelling approaches still provide essential knowledge about where and when wind erosion occurs and can disclose the level of risk for agricultural productivity in specific areas. Here, we present a geographic information system (GIS) version of the RWEQ (named GIS-RWEQ) to quantitatively assess soil loss by wind over large study areas (Land Degradation & Development, DOI: 10.1002/ldr.2588). The model designed to predict the daily soil loss potential at a ca. 1 km2 spatial resolution shows high consistency with local measurements reported in literature. The average soil loss predicted by GIS-RWEQ for the European arable land totals 62 million Mg yr-1, with an average area-specific soil loss of 0.53 Mg yr-1. The JRC model RUSLE2015, for the same area estimates 295 million Mg yr-1 of soil loss due to water erosion. Notably, soil loss by wind erosion in the European arable land could be as high as 20% of water erosion, even though the areas affected are mainly concentrated in hotspots.

Impacts of rural land-use on overland flow and sediment transport

NASA Astrophysics Data System (ADS)

Fraser, S. L.; Jackson, B. M.; Norton, K. P.

2013-12-01

The loss of fertile topsoil over time, due to erosive processes, could have a major impact on New Zealand's economy as well as being devastating to individual land owners. Improved management of land use is needed to provide protection of soil from erosion by overland flow and aeolian processes. Effects of soil erosion and sedimentation result in an annual nationwide cost of NZ$123 million. Many previous New Zealand studies have focused on large scale soil movement from land sliding and gully erosion, including identifying risk areas. However, long term small scale erosion and degradation has been largely overlooked in the literature. Although small scale soil erosion is less apparent than mass movement, cumulative small scale soil loss over many years may have a significant impact for future land productivity. One approach to assessing the role of soil degradation is through the application of landscape models. Due to the time consuming collection of data and limited scales over which data can be collected, many models created are unique to a particular land type, land use or locality. Collection of additional datasets can broaden the use of such models by informing model representation and enhancing parameterisation. The Land Use Capability Index (LUCI), developed by Jackson et al (2013) is an example of a model that will benefit from additional data sets. LUCI is a multi-criteria GIS tool, designed to inform land management decisions by identifying areas of potential change, based on land characteristics and land use options. LUCI topographically routes overland flow and sediment using existing land characteristic maps and additionally incorporating sub-field scale data. The model then has the ability to utilise these data to enhance prediction at landscape scale. This study focuses on the influence of land use on small scale sediment transport and enhancing process representation and parameterisation to improve predictive ability of models, such as LUCI. Data are currently being collected in a small catchment at the foothills of the Tararua ranges, lower North Island of New Zealand. Gurlach traps are utilised in a step like array on a number of hillslopes to provide a comprehensive dataset of overland flow and sediment volume for different magnitude rainfall events. ArcGIS is used to calculate a contributing area to each trap. The study provides quantitative data linking overland flow to event magnitude for the rural land uses of pasture versus regenerating native forest at multiple slope angles. These data along with measured soil depth/slope relationships and stream monitoring data are used to inform process representation and parameterisation of LUCI at hillslope scale. LUCI is then used to explore implications at landscape scale. The data and modelling are intended to provide information to help in long-term land management decisions. Jackson, B., Pagella, T., Sinclair, F., Orellana, B., Henshaw, A., Reynolds, B., McIntyre, N., Wheater, H., and Eycott, A. 2013. Polyscape: A GIS mapping framework providing efficient and spatially explicit landscape-scale valuation of multiple ecosystem services. Landscape and Urban Planning, 112(0): 74-88

Closing the Knowledge Gap: Effects of Land Use Conversion on Belowground Carbon near the 100th Meridian

NASA Astrophysics Data System (ADS)

Waldron, S. E.; Phillips, R. L.; Dell, R.; Suddick, E. C.

2012-12-01

Native prairie of the northern Great Plains near the 100th meridian is currently under land use conversion pressure due to high commodity prices. From 2002 to 2007, approximately 303,515 hectares of prairie were converted to crop production in the Prairie Pothole Region (PPR) from Montana to the Dakotas. The spatiotemporal effects of land-use conversion on soil organic matter are still unclear for the PPR. Effects will vary with management, soil properties and time, making regional experiments and simulation modeling necessary. Grassland conservationists are interested in soil carbon data and soil carbon simulation models to inform potential voluntary carbon credit programs. These programs require quantification of changes in soil carbon associated with land-use conversion and management. We addressed this issue by 1) designing a regional-scale experiment, 2) collecting and analyzing soil data, and 3) interviewing producers about land management practices, as required for regional, process-based biogeochemical models. We selected farms at random within a 29,000 km2 area of interest and measured soil properties at multiple depths for native prairie and adjacent annual crop fields. The cores were processed at six different depths (between 0 and 100 cm) for bulk density, pH, texture, total carbon, inorganic carbon, and total nitrogen. We found that the largest difference in soil organic carbon occurred at the 0-10 cm depth, but the magnitude of the effect of land use varied with soil properties and land management. Results from this project, coupled with regional model simulations (Denitrification-Decomposition, DNDC) represent the baseline data needed for future voluntary carbon credit programs and long-term carbon monitoring networks. Enrollment in such programs could help ranchers and farmers realize a new income stream from maintaining their native prairie and the carbon stored beneath it.

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.

Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0

DOE PAGES

Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.; ...

2016-08-25

Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate–carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimationmore » system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model–data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. Furthermore, the new improved parameters for JULES are presented along with the associated uncertainties for each parameter.« less

Effects of future climate conditions on terrestrial export from coastal southern California

NASA Astrophysics Data System (ADS)

Feng, D.; Zhao, Y.; Raoufi, R.; Beighley, E.; Melack, J. M.

2015-12-01

The Santa Barbara Coastal - Long Term Ecological Research Project (SBC-LTER) is focused on investigating the relative importance of land and ocean processes in structuring giant kelp forest ecosystems. Understanding how current and future climate conditions influence terrestrial export is a central theme for the project. Here we combine the Hillslope River Routing (HRR) model and daily precipitation and temperature downscaled using statistical downscaling based on localized constructed Analogs (LOCA) to estimate recent streamflow dynamics (2000 to 2014) and future conditions (2015 to 2100). The HRR model covers the SBC-LTER watersheds from just west of the Ventura River to Point Conception; a land area of roughly 800 km2 with 179 watersheds ranging from 0.1 to 123 km2. The downscaled climate conditions have a spatial resolution of 6 km by 6 km. Here, we use the Penman-Monteith method with the Food and Agriculture Organization of the United Nations (FAO) limited climate data approximations and land surface conditions (albedo, leaf area index, land cover) measured from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites to estimate potential evapotranspiration (PET). The HRR model is calibrated for the period 2000 to 2014 using USGS and LTER streamflow. An automated calibration technique is used. For future climate scenarios, we use mean 8-day land cover conditions. Future streamflow, ET and soil moisture statistics are presented and based on downscaled P and T from ten climate model projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5).

An analysis of airline landing flare data based on flight and training simulator measurements

NASA Technical Reports Server (NTRS)

Heffley, R. K.; Schulman, T. M.; Clement, T. M.

1982-01-01

Landings by experienced airline pilots transitioning to the DC-10, performed in flight and on a simulator, were analyzed and compared using a pilot-in-the-loop model of the landing maneuver. By solving for the effective feedback gains and pilot compensation which described landing technique, it was possible to discern fundamental differences in pilot behavior between the actual aircraft and the simulator. These differences were then used to infer simulator fidelity in terms of specific deficiencies and to quantify the effectiveness of training on the simulator as compared to training in flight. While training on the simulator, pilots exhibited larger effective lag in commanding the flare. The inability to compensate adequately for this lag was associated with hard or inconsistent landings. To some degree this deficiency was carried into flight, thus resulting in a slightly different and inferior landing technique than exhibited by pilots trained exclusively on the actual aircraft.

The impact of Surface Wind Velocity Data Assimilation on the Predictability of Plume Advection in the Lower Troposphere

NASA Astrophysics Data System (ADS)

Sekiyama, Thomas; Kajino, Mizuo; Kunii, Masaru

2017-04-01

The authors investigated the impact of surface wind velocity data assimilation on the predictability of plume advection in the lower troposphere exploiting the radioactive cesium emitted by the Fukushima nuclear accident in March 2011 as an atmospheric tracer. It was because the radioactive cesium plume was dispersed from the sole point source exactly placed at the Fukushima Daiichi Nuclear Power Plant and its surface concentration was measured at many locations with a high frequency and high accuracy. We used a non-hydrostatic regional weather prediction model with a horizontal resolution of 3 km, which was coupled with an ensemble Kalman filter data assimilation system in this study, to simulate the wind velocity and plume advection. The main module of this weather prediction model has been developed and used operationally by the Japan Meteorological Agency (JMA) since before March 2011. The weather observation data assimilated into the model simulation were provided from two data resources; [#1] the JMA observation archives collected for numerical weather predictions (NWPs) and [#2] the land-surface wind velocity data archived by the JMA surface weather observation network. The former dataset [#1] does not contain land-surface wind velocity observations because their spatial representativeness is relatively small and therefore the land-surface wind velocity data assimilation normally deteriorates the more than one day NWP performance. The latter dataset [#2] is usually used for real-time weather monitoring and never used for the data assimilation of more than one day NWPs. We conducted two experiments (STD and TEST) to reproduce the radioactive cesium plume behavior for 48 hours from 12UTC 14 March to 12UTC 16 March 2011 over the land area of western Japan. The STD experiment was performed to replicate the operational NWP using only the #1 dataset, not assimilating land-surface wind observations. In contrast, the TEST experiment was performed assimilating both the #1 dataset and the #2 dataset including land-surface wind observations measured at more than 200 stations in the model domain. The meteorological boundary conditions for both the experiments were imported from the JMA operational global NWP model results. The modeled radioactive cesium concentrations were examined for plume arrival timing at each observatory comparing with the hourly-measured "suspended particulate matter" filter tape's cesium concentrations retrieved by Tsuruta et al. at more than 40 observatories. The averaged difference of the plume arrival times at 40 observatories between the observational reality and the STD experiment was 82.0 minutes; at this time, the forecast period was 13 hours on average. Meanwhile, The averaged difference of the TEST experiment was 72.8 minutes, which was smaller than that of the STD experiment with a statistical significance of 99.2 %. In summary, the land-surface wind velocity data assimilation improves the predictability of plume advection in the lower troposphere at least in the case of wintertime air pollution over complex terrain. We need more investigation into the data assimilation impact of land-surface weather observations on the predictability of pollutant dispersion especially in the planetary boundary layer.

The hydrological cycle at European Fluxnet sites: modeling seasonal water and energy budgets at local scale.

NASA Astrophysics Data System (ADS)

Stockli, R.; Vidale, P. L.

2003-04-01

The importance of correctly including land surface processes in climate models has been increasingly recognized in the past years. Even on seasonal to interannual time scales land surface - atmosphere feedbacks can play a substantial role in determining the state of the near-surface climate. The availability of soil moisture for both runoff and evapotranspiration is dependent on biophysical processes occuring in plants and in the soil acting on a wide time-scale from minutes to years. Fluxnet site measurements in various climatic zones are used to drive three generations of LSM's (land surface models) in order to assess the level of complexity needed to represent vegetation processes at the local scale. The three models were the Bucket model (Manabe 1969), BATS 1E (Dickinson 1984) and SiB 2 (Sellers et al. 1996). Evapotranspiration and runoff processes simulated by these models range from simple one-layer soils and no-vegetation parameterizations to complex multilayer soils, including realistic photosynthesis-stomatal conductance models. The latter is driven by satellite remote sensing land surface parameters inheriting the spatiotemporal evolution of vegetation phenology. In addition a simulation with SiB 2 not only including vertical water fluxes but also lateral soil moisture transfers by downslope flow is conducted for a pre-alpine catchment in Switzerland. Preliminary results are presented and show that - depending on the climatic environment and on the season - a realistic representation of evapotranspiration processes including seasonally and interannually-varying state of vegetation is significantly improving the representation of observed latent and sensible heat fluxes on the local scale. Moreover, the interannual evolution of soil moisture availability and runoff is strongly dependent on the chosen model complexity. Biophysical land surface parameters from satellite allow to represent the seasonal changes in vegetation activity, which has great impact on the yearly budget of transpiration fluxes. For some sites, however, the hydrological cycle is simulated reasonably well even with simple land surface representations.

Projecting land-use change and its consequences for biodiversity in northern Thailand.

PubMed

Trisurat, Yongyut; Alkemade, Rob; Verburg, Peter H

2010-03-01

Rapid deforestation has occurred in northern Thailand over the last few decades and it is expected to continue. The government has implemented conservation policies aimed at maintaining forest cover of 50% or more and promoting agribusiness, forestry, and tourism development in the region. The goal of this paper was to analyze the likely effects of various directions of development on the region. Specific objectives were (1) to forecast land-use change and land-use patterns across the region based on three scenarios, (2) to analyze the consequences for biodiversity, and (3) to identify areas most susceptible to future deforestation and high biodiversity loss. The study combined a dynamic land-use change model (Dyna-CLUE) with a model for biodiversity assessment (GLOBIO3). The Dyna-CLUE model was used to determine the spatial patterns of land-use change for the three scenarios. The methodology developed for the Global Biodiversity Assessment Model framework (GLOBIO 3) was used to estimate biodiversity intactness expressed as the remaining relative mean species abundance (MSA) of the original species relative to their abundance in the primary vegetation. The results revealed that forest cover in 2050 would mainly persist in the west and upper north of the region, which is rugged and not easily accessible. In contrast, the highest deforestation was expected to occur in the lower north. MSA values decreased from 0.52 in 2002 to 0.45, 0.46, and 0.48, respectively, for the three scenarios in 2050. In addition, the estimated area with a high threat to biodiversity (an MSA decrease >0.5) derived from the simulated land-use maps in 2050 was approximately 2.8% of the region for the trend scenario. In contrast, the high-threat areas covered 1.6 and 0.3% of the region for the integrated-management and conservation-oriented scenarios, respectively. Based on the model outcomes, conservation measures were recommended to minimize the impacts of deforestation on biodiversity. The model results indicated that only establishing a fixed percentage of forest was not efficient in conserving biodiversity. Measures aimed at the conservation of locations with high biodiversity values, limited fragmentation, and careful consideration of road expansion in pristine forest areas may be more efficient to achieve biodiversity conservation.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Evaluating the influence of plant-specific physiological parameterizations on the partitioning of land surface energy fluxes

NASA Astrophysics Data System (ADS)

Sulis, Mauro; Langensiepen, Matthias; Shrestha, Prabhakar; Schickling, Anke; Simmer, Clemens; Kollet, Stefan

2015-04-01

Vegetation has a significant influence on the partitioning of radiative forcing, the spatial and temporal variability of soil water and soil temperature. Therefore plant physiological properties play a key role in mediating and amplifying interactions and feedback mechanisms in the soil-vegetation-atmosphere continuum. Because of the direct impact on latent heat fluxes, these properties may also influence weather generating processes, such as the evolution of the atmospheric boundary layer (ABL). In land surface models, plant physiological properties are usually obtained from literature synthesis by unifying several plant/crop species in predefined vegetation classes. In this work, crop-specific physiological characteristics, retrieved from detailed field measurements, are included in the bio-physical parameterization of the Community Land Model (CLM), which is a component of the Terrestrial Systems Modeling Platform (TerrSysMP). The measured set of parameters for two typical European mid-latitudinal crops (sugar beet and winter wheat) is validated using eddy covariance measurements (sensible heat and latent heat) over multiple years from three measurement sites located in the North Rhine-Westphalia region, Germany. We found clear improvements of CLM simulations, when using the crop-specific physiological characteristics of the plants instead of the generic crop type when compared to the measurements. In particular, the increase of latent heat fluxes in conjunction with decreased sensible heat fluxes as simulated by the two new crop-specific parameter sets leads to an improved quantification of the diurnal energy partitioning. These findings are cross-validated using estimates of gross primary production extracted from net ecosystem exchange measurements. This independent analysis reveals that the better agreement between observed and simulated latent heat using the plant-specific physiological properties largely stems from an improved simulation of the photosynthesis process owing to a better estimation of the Rubisco enzyme kinematics. Finally, to evaluate the effects of the crop-specific parameterizations on the ABL dynamics, we perform a series of semi-idealized land-atmosphere coupled simulations by hypothesizing three cropland configurations. These numerical experiments reveal different heat and moisture budgets of the ABL that clearly impact the evolution of the boundary layer when using the crop-specific physiological properties.

Entry, Descent, and Landing Aerothermodynamics: NASA Langley Experimental Capabilities and Contributions

NASA Technical Reports Server (NTRS)

Hollis, Brian R.; Berger, Karen T.; Berry, Scott A.; Bruckmann, Gregory J.; Buck, Gregory M.; DiFulvio, Michael; Horvath, Thomas J.; Liechty, Derek S.; Merski, N. Ronald; Murphy, Kelly J.;

Adjusting measured peak discharges from an urbanizing watershed to reflect a stationary land use signal

NASA Astrophysics Data System (ADS)

Beighley, R. Edward; Moglen, Glenn E.

2003-04-01

A procedure to adjust gauged streamflow data from watersheds urbanized during or after their gauging period is presented. The procedure adjusts streamflow to be representative of a fixed land use condition, which may reflect current or future development conditions. Our intent is to determine what an event resulting in a peak discharge in, for example, 1950 (i.e., before urbanization) would produce on the current urban watershed. While past approaches assumed uniform spatial and temporal changes in urbanization, this study focuses on the use of geographic information systems (GIS) based methodologies for precisely locating in space and time where land use change has occurred. This information is incorporated into a hydrologic model to simulate the change in discharge as a result of changing land use conditions. In this paper, we use historical aerial photographs, GIS linked tax-map data, and recent land use/land cover data to recreate the spatial development history of eight gauged watersheds in the Baltimore-Washington, D. C., metropolitan area. Using our procedure to determine discharge series representative of the current urban watersheds, we found that the increase of the adjusted 2-year discharge ranged from 16 to 70 percent compared with the measured annual maximum discharge series. For the 100-year discharge the adjusted values ranged from 0 to 47 percent greater than the measured values. Additionally, relationships between the increase in flood flows and four measures of urbanization (increase in urban land, decrease in forested land, increase in high-density development, and the spatial development pattern) are investigated for predicting the increase in flood flows for ungauged watersheds. Watersheds with the largest increases in flood flows typically had more extensive development in the areas far removed from the outlet. In contrast, watersheds with development located nearer to the outlet typically had the smallest increases in peak discharge.

Land Use, Residential Density, and Walking

PubMed Central

Rodríguez, Daniel A.; Evenson, Kelly R.; Diez Roux, Ana V.; Brines, Shannon J.

2009-01-01

Background The neighborhood environment may play a role in encouraging sedentary patterns, especially for middle-aged and older adults. Purpose Associations between walking and neighborhood population density, retail availability, and land use distribution were examined using data from a cohort of adults aged 45 to 84 years old. Methods Data from a multi-ethnic sample of 5529 adult residents of Baltimore MD, Chicago IL, Forsyth County NC, Los Angeles CA, New York NY, and St. Paul MN, enrolled in the Multi-Ethnic Study of Atherosclerosis in 2000–2002 were linked to secondary land use and population data. Participant reports of access to destinations and stores and objective measures of the percentage of land area in parcels devoted to retail land uses, the population divided by land area in parcels, and the mixture of uses for areas within 200m of each participant's residence were examined. Multinomial logistic regression was used to investigate associations of self-reported and objective neighborhood characteristics with walking. All analyses were conducted in 2008 and 2009. Results After adjustment for individual-level characteristics and neighborhood connectivity, higher density, greater land area devoted to retail uses, and self-reported measures of proximity of destinations and ease of walking to places were each related to walking. In models including all land use measures, population density was positively associated with walking to places and with walking for exercise for more than 90 min/wk both relative to no walking. Availability of retail was associated with walking to places relative to not walking, having a more proportional mix of land uses was associated with walking for exercise for more than 90 min/wk, while self-reported ease of access to places was related to higher levels of exercise walking both relative to not walking. Conclusions Residential density and the presence of retail uses are related to various walking behaviors. Efforts to increase walking may benefit from attention to the intensity and type of land development. PMID:19840694

Investigation of wear land and rate of locally made HSS cutting tool

NASA Astrophysics Data System (ADS)

Afolalu, S. A.; Abioye, A. A.; Dirisu, J. O.; Okokpujie, I. P.; Ajayi, O. O.; Adetunji, O. R.

2018-04-01

Production technology and machining are inseparable with cutting operation playing important roles. Investigation of wear land and rate of cutting tool developed locally (C=0.56%) with an HSS cutting tool (C=0.65%) as a control was carried out. Wear rate test was carried out using Rotopol -V and Impact tester. The samples (12) of locally made cutting tools and one (1) sample of a control HSS cutting tool were weighed to get the initial weight and grit was fixed at a point for the sample to revolve at a specific time of 10 mins interval. Approach of macro transfer particles that involved mechanism of abrasion and adhesion which was termed as mechanical wear to handle abrasion adhesion processes was used in developing equation for growth wear at flank. It was observed from the wear test that best minimum wear rate of 1.09 × 10-8 and 2.053 × 10-8 for the tools developed and control were measured. MATLAB was used to simulate the wear land and rate under different conditions. Validated results of both the experimental and modeling showed that cutting speed has effect on wear rate while cutting time has predicted measure on wear land. Both experimental and modeling result showed best performances of tools developed over the control.

A Monte Carlo approach to the inverse problem of diffuse pollution risk in agricultural catchments

NASA Astrophysics Data System (ADS)

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

2012-04-01

The hydrological and biogeochemical processes that operate in catchments influence the ecological quality of freshwater systems through delivery of fine sediment, nutrients and organic matter. As an alternative to the, often complex, reductionist models we outline a - data-driven - approach based on 'inverse modelling'. We invert SCIMAP, a parsimonious risk based model that has an explicit treatment of hydrological connectivity, and use a Bayesian approach to determine the risk that must be assigned to different land uses in a catchment in order to explain the spatial patterns of measured in-stream nutrient concentrations. First, we apply the model to a set of eleven UK catchments to show that: 1) some land use generates a consistently high or low risk of diffuse nitrate (N) and Phosphate (P) pollution; but 2) the risks associated with different land uses vary both between catchments and between P and N delivery; and 3) that the dominant sources of P and N risk in the catchment are often a function of the spatial configuration of land uses. These results suggest that on a case by case basis, inverse modelling may be used to help prioritise the focus of interventions to reduce diffuse pollution risk for freshwater ecosystems. However, a key uncertainty in this approach is the extent to which it can recover the 'true' risks associated with a land cover given error in both the input parameters and equifinality in model outcomes. We test this using a set of synthetic scenarios in which the true risks can be pre-assigned then compared with those recovered from the inverse model. We use these scenarios to identify the number of simulations and observations required to optimize recovery of the true weights, then explore the conditions under which the inverse model becomes equifinal (hampering recovery of the true weights) We find that this is strongly dependent on the covariance in land covers between subcatchments, introducing the possibility that instream sampling could be designed or subsampled to maximize identifiability of the risks associated with a given land cover.

Quantifying soil profile change caused by land use in central Missouri loess hillslopes

Treesearch

Samuel J. Indorante; John M. Kabrick; Brad D. Lee; Jon M. Maatta

2014-01-01

Three major challenges are present when studying anthropogenic impacts on soil profile properties: (i) site selection; (ii) sampling and modeling native and cultivated soil-landscape relationships; and (iii) graphically and statistically comparing native and cultivated sites to model soil profile changes. This study addressed those challenges by measuring and modeling...

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Surface knowledge and risks to landing and roving - The scale problem

NASA Technical Reports Server (NTRS)

Bourke, Roger D.

1991-01-01

The role of surface information in the performance of surface exploration missions is discussed. Accurate surface models based on direct measurements or inference are considered to be an important component in mission risk management. These models can be obtained using high resolution orbital photography or a combination of laser profiling, thermal inertia measurements, and/or radar. It is concluded that strategies for Martian exploration should use high confidence models to achieve maximum performance and low risk.

Eco-hydrological Responses to Soil and Water Conservation in the Jinghe River Basin

NASA Astrophysics Data System (ADS)

Peng, H.; Jia, Y.; Qiu, Y.

2011-12-01

The Jinghe River Basin is one of the most serious soil erosion areas in the Loess Plateau. Many measures of soil and water conservation were applied in the basin. Terrestrial ecosystem model BIOME-BGC and distributed hydrological model WEP-L were used to build eco-hydrological model and verified by field observation and literature values. The model was applied in the Jinghe River Basin to analyze eco-hydrological responses under the scenarios of vegetation type change due to soil and water conservation polices. Four scenarios were set under the measures of conversion of cropland to forest, forestation on bare land, forestation on slope wasteland and planting grass on bare land. Analysis results show that the soil and water conservation has significant effects on runoff and the carbon cycle in the Jinghe River Basin: the average annual runoff would decrease and the average annual NPP and carbon storage would increase. Key words: soil and water conservation; conversion of cropland to forest; eco-hydrology response; the Jinghe River Basin

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

PubMed

van Asselen, Sanneke; Verburg, Peter H

2013-12-01

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

Crash Testing and Simulation of a Cessna 172 Aircraft: Hard Landing Onto Concrete

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Fasanella, Edwin L.

2016-01-01

A full-scale crash test of a Cessna 172 aircraft was conducted at the Landing and Impact Research Facility at NASA Langley Research Center during the summer of 2015. The purpose of the test was to evaluate the performance of Emergency Locator Transmitters (ELTs) that were mounted at various locations in the aircraft and to generate impact test data for model validation. A finite element model of the aircraft was developed for execution in LSDYNA to simulate the test. Measured impact conditions were 722.4-in/s forward velocity and 276-in/s vertical velocity with a 1.5deg pitch (nose up) attitude. These conditions were intended to represent a survivable hard landing. The impact surface was concrete. During the test, the nose gear tire impacted the concrete, followed closely by impact of the main gear tires. The main landing gear spread outward, as the nose gear stroked vertically. The only fuselage contact with the impact surface was a slight impact of the rearmost portion of the lower tail. Thus, capturing the behavior of the nose and main landing gear was essential to accurately predict the response. This paper describes the model development and presents test-analysis comparisons in three categories: inertial properties, time sequence of events, and acceleration and velocity time-histories.

Modeling evapotranspiration over China's landmass from 1979-2012 using three surface models

NASA Astrophysics Data System (ADS)

Sun, Shaobo; Chen, Baozhang; Zhang, Huifang; Lin, Xiaofeng

2017-04-01

Land surface models (LSMs) are useful tools to estimate land evapotranspiration at a grid scale and for a long-term applications. Here, the Community Land Model 4.0 (CLM4.0), Dynamic Land Model (DLM) and Variable Infiltration Capacity (VIC) model were driven with observation-based forcing data sets, and a multiple LSM ensemble-averaged evapotranspiration (ET) product (LSMs-ET) was developed and its spatial-temporal variations were analyzed for the China landmass over the period 1979-2012. Evaluations against measurements from nine flux towers at site scale and surface water budget based ET at regional scale showed that the LSMs-ET had good performance in most areas of China's landmass. The inter-comparisons between the ET estimates and the independent ET products from remote sensing and upscaling methods suggested that there were a fairly consistent patterns between each data sets. The LSMs-ET produced a mean annual ET of 351.24±10.7 mm yr-1 over 1979-2012, and its spatial-temporal variation analyses showed that (i) there was an overall significant ET increasing trend, with a value of 0.72 mm yr-1 (p < 0.01); (ii) 36.01% of Chinese land had significant increasing trends, ranging from 1 to 9 mm yr-1, while only 6.41% of the area showed significant decreasing trends, ranging from -6.28 to -0.08 mm yr-1. Analyses of ET variations in each climate region clearly showed that the Tibetan Plateau areas were the main contributors to the overall increasing ET trends of China.

Degradation of net primary production in a semiarid rangeland

NASA Astrophysics Data System (ADS)

Jackson, Hasan; Prince, Stephen D.

2016-08-01

Anthropogenic land degradation affects many biogeophysical processes, including reductions of net primary production (NPP). Degradation occurs at scales from small fields to continental and global. While measurement and monitoring of NPP in small areas is routine in some studies, for scales larger than 1 km2, and certainly global, there is no regular monitoring and certainly no attempt to measure degradation. Quantitative and repeatable techniques to assess the extent of deleterious effects and monitor changes are needed to evaluate its effects on, for example, economic yields of primary products such as crops, lumber, and forage, and as a measure of land surface properties which are currently missing from dynamic global vegetation models, assessments of carbon sequestration, and land surface models of heat, water, and carbon exchanges. This study employed the local NPP scaling (LNS) approach to identify patterns of anthropogenic degradation of NPP in the Burdekin Dry Tropics (BDT) region of Queensland, Australia, from 2000 to 2013. The method starts with land classification based on the environmental factors presumed to control (NPP) to group pixels having similar potential NPP. Then, satellite remotely sensing data were used to compare actual NPP with its potential. The difference in units of mass of carbon and percentage loss were the measure of degradation. The entire BDT (7.45 × 106 km2) was investigated at a spatial resolution of 250 × 250 m. The average annual reduction in NPP due to anthropogenic land degradation in the entire BDT was -2.14 MgC m-2 yr-1, or 17 % of the non-degraded potential, and the total reduction was -214 MgC yr-1. Extreme average annual losses of 524.8 gC m-2 yr-1 were detected. Approximately 20 % of the BDT was classified as "degraded". Varying severities and rates of degradation were found among the river basins, of which the Belyando and Suttor were highest. Interannual, negative trends in reductions of NPP occurred in 7 % of the entire region, indicating ongoing degradation. There was evidence of areas that were in a permanently degraded condition. The findings provide strong evidence and quantitative data for reductions in NPP related to anthropogenic land degradation in the BDT.

Identification of anthropogenic impact on nitrogen cycling using stable isotopes and distibuted hydrologic modeling

NASA Astrophysics Data System (ADS)

Macko, S. A.; O'Connell, M. T.; Fu, Y.

2016-12-01

The Najinhe watershed is a topographically diverse, heavily agricultural watershed in northeastern China that provides opportunities for identification of the impact of land use on nitrogen cycling. Land use, both historic and current, influences the biological processing of nitrogen in a particular area. Soil conditions, including moisture, texture, and organic content, control the capacity of a parcel for processing reactive nitrogen. Compounds derived from natural and anthropogenic sources exhibit characteristic ratios of stable isotopes of nitrogen and oxygen that serve as tracers of origin as well as integrators of biological processes. A distributed hydrologic model coupled with one focusing on reactive transport is able to help determine locations with the highest impact on the dissolved N in this system. Gaussian Markov Random Fields were used to determine the biogeochemical influence of model locations whereas δ15N measurements from NO3- and NH4+ in soil extracts were used to calibrate and validate model predictions based on measured precipitation and streamflow values. Sources were integrated using a Bayesian mixing model to determine likely fate and transport parameters for various N inputs to the watershed. The application of the coupled hydrologic and transport models to a village scale catchment suggests integration and expansion to larger watersheds on the basin scale. Identification of sensitive parcels on multiple spatial scales can direct targeted land management efforts to mitigate ecological and health effects of reactive N in surface waters.

Systematic Mapping and Statistical Analyses of Valley Landform and Vegetation Asymmetries Across Hydroclimatic Gradients

NASA Astrophysics Data System (ADS)

Poulos, M. J.; Pierce, J. L.; McNamara, J. P.; Flores, A. N.; Benner, S. G.

2015-12-01

Terrain aspect alters the spatial distribution of insolation across topography, driving eco-pedo-hydro-geomorphic feedbacks that can alter landform evolution and result in valley asymmetries for a suite of land surface characteristics (e.g. slope length and steepness, vegetation, soil properties, and drainage development). Asymmetric valleys serve as natural laboratories for studying how landscapes respond to climate perturbation. In the semi-arid montane granodioritic terrain of the Idaho batholith, Northern Rocky Mountains, USA, prior works indicate that reduced insolation on northern (pole-facing) aspects prolongs snow pack persistence, and is associated with thicker, finer-grained soils, that retain more water, prolong the growing season, support coniferous forest rather than sagebrush steppe ecosystems, stabilize slopes at steeper angles, and produce sparser drainage networks. We hypothesize that the primary drivers of valley asymmetry development are changes in the pedon-scale water-balance that coalesce to alter catchment-scale runoff and drainage development, and ultimately cause the divide between north and south-facing land surfaces to migrate northward. We explore this conceptual framework by coupling land surface analyses with statistical modeling to assess relationships and the relative importance of land surface characteristics. Throughout the Idaho batholith, we systematically mapped and tabulated various statistical measures of landforms, land cover, and hydroclimate within discrete valley segments (n=~10,000). We developed a random forest based statistical model to predict valley slope asymmetry based upon numerous measures (n>300) of landscape asymmetries. Preliminary results suggest that drainages are tightly coupled with hillslopes throughout the region, with drainage-network slope being one of the strongest predictors of land-surface-averaged slope asymmetry. When slope-related statistics are excluded, due to possible autocorrelation, valley slope asymmetry is most strongly predicted by asymmetries of insolation and drainage density, which generally supports a water-balance based conceptual model of valley asymmetry development. Surprisingly, vegetation asymmetries had relatively low predictive importance.

The future of irrigated agriculture under environmental flow requirements restrictions

NASA Astrophysics Data System (ADS)

Pastor, Amandine; Palazzo, Amanda; Havlik, Petr; Kabat, Pavel; Obersteiner, Michael; Ludwig, Fulco

2016-04-01

Water is not an infinite resource and demand from irrigation, household and industry is constantly increasing. This study focused on including global water availability including environmental flow requirements with water withdrawal from irrigation and other sectors at a monthly time-step in the GLOBIOM model. This model allows re-adjustment of land-use allocation, crop management, consumption and international trade. The GLOBIOM model induces an endogenous change in water price depending on water supply and demand. In this study, the focus was on how the inclusion of water resources affects land-use and, in particular, how global change will influence repartition of irrigated and rainfed lands at global scale. We used the climate change scenario including a radiative forcing of 8.5 W/m2 (RCP8.5), the socio-economic scenario (SSP2: middle-of-road), and the environmental flow method based on monthly flow allocation (the Variable Monthly Flow method) with high and low restrictions. Irrigation withdrawals were adjusted to a monthly time-step to account for biophysical water limitations at finer time resolution. Our results show that irrigated land might decrease up to 40% on average depending on the choice of EFR restrictions. Several areas were identified as future hot-spots of water stress such as the Mediterranean and Middle-East regions. Other countries were identified to be in safe position in terms of water stress such as North-European countries. Re-allocation of rainfed and irrigated land might be useful information for land-use planners and water managers at an international level to decide on appropriate legislations on climate change mitigation/adaptation when exposure and sensitivity to climate change is high and/or on adaptation measures to face increasing water demand. For example, some countries are likely to adopt measures to increase their water use efficiencies (irrigation system, soil and water conservation practices) to face water shortages, while others might consider improving their trade policy to avoid food shortage.

Balancing food security and water demand for freshwater ecosystems

NASA Astrophysics Data System (ADS)

Pastor, Amandine; Palazzo, Amanda; Havlik, Petr; Obersteiner, Michael; Biemans, Hester; Wada, Yoshihide; Kabat, Pavel; Ludwig, Fulco

2017-04-01

Water is not an infinite resource and demand from irrigation, household and industry is constantly increasing. This study focused on including global water availability including environmental flow requirements with water withdrawal from irrigation and other sectors at a monthly time-step in the GLOBIOM model. This model allows re-adjustment of land-use allocation, crop management, consumption and international trade. The GLOBIOM model induces an endogenous change in water price depending on water supply and demand. In this study, the focus was on how the inclusion of water resources affects land-use and, in particular, how global change will influence repartition of irrigated and rainfed lands at global scale. We used the climate change scenario including a radiative forcing of 8.5 W/m2 (RCP8.5), the socio-economic scenario (SSP2: middle-of-road), and the environmental flow method based on monthly flow allocation (the Variable Monthly Flow method) with high and low restrictions. Irrigation withdrawals were adjusted to a monthly time-step to account for biophysical water limitations at finer time resolution. Our results show that irrigated land might decrease up to 40% on average depending on the choice of EFR restrictions. Several areas were identified as future hot-spots of water stress such as the Mediterranean and Middle-East regions. Other countries were identified to be in safe position in terms of water stress such as North-European countries. Re-allocation of rainfed and irrigated land might be useful information for land-use planners and water managers at an international level to decide on appropriate legislations on climate change mitigation/adaptation when exposure and sensitivity to climate change is high and/or on adaptation measures to face increasing water demand. For example, some countries are likely to adopt measures to increase their water use efficiencies (irrigation system, soil and water conservation practices) to face water shortages, while others might consider improving their trade policy to avoid food shortage.

Integrating environmental and socio-economic indicators of a linked catchment-coastal system using variable environmental intensity.

PubMed

Dymond, John R; Davie, Tim J A; Fenemor, Andrew D; Ekanayake, Jagath C; Knight, Ben R; Cole, Anthony O; de Oca Munguia, Oscar Montes; Allen, Will J; Young, Roger G; Basher, Les R; Dresser, Marc; Batstone, Chris J

2010-09-01

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic-and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.

Integrating Environmental and Socio-Economic Indicators of a Linked Catchment-Coastal System Using Variable Environmental Intensity

NASA Astrophysics Data System (ADS)

Dymond, John R.; Davie, Tim J. A.; Fenemor, Andrew D.; Ekanayake, Jagath C.; Knight, Ben R.; Cole, Anthony O.; de Oca Munguia, Oscar Montes; Allen, Will J.; Young, Roger G.; Basher, Les R.; Dresser, Marc; Batstone, Chris J.

2010-09-01

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic—and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality ( E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.

Land Capability Potential Index (LCPI) for the Lower Missouri River Valley

USGS Publications Warehouse

Jacobson, Robert B.; Chojnacki, Kimberly A.; Reuter, Joanna M.

2007-01-01

The Land Capability Potential Index (LCPI) was developed to serve as a relatively coarse-scale index to delineate broad land capability classes in the valley of the Lower Missouri River. The index integrates fundamental factors that determine suitability of land for various uses, and may provide a useful mechanism to guide land-management decisions. The LCPI was constructed from integration of hydrology, hydraulics, land-surface elevations, and soil permeability (or saturated hydraulic conductivity) datasets for an area of the Lower Missouri River, river miles 423–670. The LCPI estimates relative wetness based on intersecting water-surface elevations, interpolated from measurements or calculated from hydraulic models, with a high-resolution land-surface elevation dataset. The potential for wet areas to retain or drain water is assessed using soil-drainage classes that are estimated from saturated hydraulic conductivity of surface soils. Terrain mapping that delineates areas with convex, concave, and flat parts of the landscape provides another means to assess tendency of landscape patches to retain surface water.

A method for coupling a parameterization of the planetary boundary layer with a hydrologic model

NASA Technical Reports Server (NTRS)

Lin, J. D.; Sun, Shu Fen

1986-01-01

Deardorff's parameterization of the planetary boundary layer is adapted to drive a hydrologic model. The method converts the atmospheric conditions measured at the anemometer height at one site to the mean values in the planetary boundary layer; it then uses the planetary boundary layer parameterization and the hydrologic variables to calculate the fluxes of momentum, heat and moisture at the atmosphere-land interface for a different site. A simplified hydrologic model is used for a simulation study of soil moisture and ground temperature on three different land surface covers. The results indicate that this method can be used to drive a spatially distributed hydrologic model by using observed data available at a meteorological station located on or nearby the site.

Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches

NASA Astrophysics Data System (ADS)

Brokamp, Cole; Jandarov, Roman; Rao, M. B.; LeMasters, Grace; Ryan, Patrick

2017-02-01

Exposure assessment for elemental components of particulate matter (PM) using land use modeling is a complex problem due to the high spatial and temporal variations in pollutant concentrations at the local scale. Land use regression (LUR) models may fail to capture complex interactions and non-linear relationships between pollutant concentrations and land use variables. The increasing availability of big spatial data and machine learning methods present an opportunity for improvement in PM exposure assessment models. In this manuscript, our objective was to develop a novel land use random forest (LURF) model and compare its accuracy and precision to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio. PM smaller than 2.5 μm (PM2.5) and eleven elemental components were measured at 24 sampling stations from the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Over 50 different predictors associated with transportation, physical features, community socioeconomic characteristics, greenspace, land cover, and emission point sources were used to construct LUR and LURF models. Cross validation was used to quantify and compare model performance. LURF and LUR models were created for aluminum (Al), copper (Cu), iron (Fe), potassium (K), manganese (Mn), nickel (Ni), lead (Pb), sulfur (S), silicon (Si), vanadium (V), zinc (Zn), and total PM2.5 in the CCAAPS study area. LURF utilized a more diverse and greater number of predictors than LUR and LURF models for Al, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all showed a decrease in fractional predictive error of at least 5% compared to their LUR models. LURF models for Al, Cu, Fe, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all had a cross validated fractional predictive error less than 30%. Furthermore, LUR models showed a differential exposure assessment bias and had a higher prediction error variance. Random forest and other machine learning methods may provide more accurate exposure assessment.

Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches.

PubMed

Brokamp, Cole; Jandarov, Roman; Rao, M B; LeMasters, Grace; Ryan, Patrick

2017-02-01

Exposure assessment for elemental components of particulate matter (PM) using land use modeling is a complex problem due to the high spatial and temporal variations in pollutant concentrations at the local scale. Land use regression (LUR) models may fail to capture complex interactions and non-linear relationships between pollutant concentrations and land use variables. The increasing availability of big spatial data and machine learning methods present an opportunity for improvement in PM exposure assessment models. In this manuscript, our objective was to develop a novel land use random forest (LURF) model and compare its accuracy and precision to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio. PM smaller than 2.5 μm (PM2.5) and eleven elemental components were measured at 24 sampling stations from the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Over 50 different predictors associated with transportation, physical features, community socioeconomic characteristics, greenspace, land cover, and emission point sources were used to construct LUR and LURF models. Cross validation was used to quantify and compare model performance. LURF and LUR models were created for aluminum (Al), copper (Cu), iron (Fe), potassium (K), manganese (Mn), nickel (Ni), lead (Pb), sulfur (S), silicon (Si), vanadium (V), zinc (Zn), and total PM2.5 in the CCAAPS study area. LURF utilized a more diverse and greater number of predictors than LUR and LURF models for Al, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all showed a decrease in fractional predictive error of at least 5% compared to their LUR models. LURF models for Al, Cu, Fe, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all had a cross validated fractional predictive error less than 30%. Furthermore, LUR models showed a differential exposure assessment bias and had a higher prediction error variance. Random forest and other machine learning methods may provide more accurate exposure assessment.

Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches

PubMed Central

Brokamp, Cole; Jandarov, Roman; Rao, M.B.; LeMasters, Grace; Ryan, Patrick

2017-01-01

Exposure assessment for elemental components of particulate matter (PM) using land use modeling is a complex problem due to the high spatial and temporal variations in pollutant concentrations at the local scale. Land use regression (LUR) models may fail to capture complex interactions and non-linear relationships between pollutant concentrations and land use variables. The increasing availability of big spatial data and machine learning methods present an opportunity for improvement in PM exposure assessment models. In this manuscript, our objective was to develop a novel land use random forest (LURF) model and compare its accuracy and precision to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio. PM smaller than 2.5 μm (PM2.5) and eleven elemental components were measured at 24 sampling stations from the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Over 50 different predictors associated with transportation, physical features, community socioeconomic characteristics, greenspace, land cover, and emission point sources were used to construct LUR and LURF models. Cross validation was used to quantify and compare model performance. LURF and LUR models were created for aluminum (Al), copper (Cu), iron (Fe), potassium (K), manganese (Mn), nickel (Ni), lead (Pb), sulfur (S), silicon (Si), vanadium (V), zinc (Zn), and total PM2.5 in the CCAAPS study area. LURF utilized a more diverse and greater number of predictors than LUR and LURF models for Al, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all showed a decrease in fractional predictive error of at least 5% compared to their LUR models. LURF models for Al, Cu, Fe, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all had a cross validated fractional predictive error less than 30%. Furthermore, LUR models showed a differential exposure assessment bias and had a higher prediction error variance. Random forest and other machine learning methods may provide more accurate exposure assessment. PMID:28959135

Modification of Roberts' Theory for Rocket Exhaust Plumes Eroding Lunar Soil

NASA Technical Reports Server (NTRS)

Metzger, Philip T.; Lane, John E.; Immer, Christopher D.

2008-01-01

Roberts' model of lunar soil erosion beneath a landing rocket has been updated in several ways to predict the effects of future lunar landings. The model predicts, among other things, the number of divots that would result on surrounding hardware due to the impact of high velocity particulates, the amount and depth of surface material removed, the volume of ejected soil, its velocity, and the distance the particles travel on the Moon. The results are compared against measured results from the Apollo program and predictions are made for mitigating the spray around a future lunar outpost.

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

NASA Astrophysics Data System (ADS)

Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry

2017-05-01

In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

Land Surface Temperature Measurements from EOS MODIS Data

NASA Technical Reports Server (NTRS)

Wan, Zhengming

1997-01-01

We made modifications to the linear kernel bidirectional reflectance distribution function (BRDF) models from Roujean et al. and Wanner et al. that extend the spectral range into the thermal infrared (TIR). With these TIR BRDF models and the IGBP land-cover product, we developed a classification-based emissivity database for the EOS/MODIS land-surface temperature (LST) algorithm and used it in version V2.0 of the MODIS LST code. Two V2.0 LST codes have been delivered to the MODIS SDST, one for the daily L2 and L3 LST products, and another for the 8-day 1km L3 LST product. New TIR thermometers (broadband radiometer with a filter in the 10-13 micron window) and an IR camera have been purchased in order to reduce the uncertainty in LST field measurements due to the temporal and spatial variations in LST. New improvements have been made to the existing TIR spectrometer in order to increase its accuracy to 0.2 C that will be required in the vicarious calibration of the MODIS TIR bands.

Steepness of Slopes at the Luna-Glob Landing Sites: Estimating by the Shaded Area Percentage in the LROC NAC Images

NASA Astrophysics Data System (ADS)

Krasilnikov, S. S.; Basilevsky, A. T.; Ivanov, M. A.; Abdrakhimov, A. M.; Kokhanov, A. A.

2018-03-01

The paper presents estimates of the occurrence probability of slopes, whose steep surfaces could be dangerous for the landing of the Luna-Glob descent probe ( Luna-25) given the baseline of the span between the landing pads ( 3.5 m), for five potential landing ellipses. As a rule, digital terrain models built from stereo pairs of high-resolution images (here, the images taken by the Narrow Angle Camera onboard the Lunar Reconnaissance Orbiter (LROC NAC)) are used in such cases. However, the planned landing sites are at high latitudes (67°-74° S), which makes it impossible to build digital terrain models, since the difference in the observation angle of the overlapping images is insufficient at these latitudes. Because of this, to estimate the steepness of slopes, we considered the interrelation between the shaded area percentage in the image and the Sun angle over horizon at the moment of imaging. For five proposed landing ellipses, the LROC NAC images (175 images in total) with a resolution from 0.4 to 1.2 m/pixel were analyzed. From the results of the measurements in each of the ellipses, the dependence of the shaded area percentage on the solar angle were built, which was converted to the occurrence probability of slopes. For this, the data on the Apollo 16 landing region ware used, which is covered by both the LROC NAC images and the digital terrain model with high resolution. As a result, the occurrence probability of slopes with different steepness has been estimated on the baseline of 3.5 m for five landing ellipses according to the steepness categories of <7°, 7°-10°, 10°-15°, 15°-20°, and >20°.

EPA Office of Water (OW): 2002 SPARROW Total NP (Catchments)

EPA Pesticide Factsheets

SPARROW (SPAtially Referenced Regressions On Watershed attributes) is a watershed modeling tool with output that allows the user to interpret water quality monitoring data at the regional and sub-regional scale. The model relates in-stream water-quality measurements to spatially referenced characteristics of watersheds, including pollutant sources and environmental factors that affect rates of pollutant delivery to streams from the land and aquatic, in-stream processing . The core of the model consists of a nonlinear regression equation describing the non-conservative transport of contaminants from point and non-point (or ??diffuse??) sources on land to rivers and through the stream and river network. SPARROW estimates contaminant concentrations, loads (or ??mass,?? which is the product of concentration and streamflow), and yields in streams (mass of nitrogen and of phosphorus entering a stream per acre of land). It empirically estimates the origin and fate of contaminants in streams and receiving bodies, and quantifies uncertainties in model predictions. The model predictions are illustrated through detailed maps that provide information about contaminant loadings and source contributions at multiple scales for specific stream reaches, basins, or other geographic areas.

Development of Semi-distributed ecohydrological model in the Rio Grande De Manati River Basin, Puerto Rico

NASA Astrophysics Data System (ADS)

Setegn, S. G.; Ortiz, J.; Melendez, J.; Barreto, M.; Torres-Perez, J. L.; Guild, L. S.

2015-12-01

There are limited studies in Puerto Rico that shows the water resources availability and variability with respect to changing climates and land use. The main goal of the HICE-PR (Human Impacts to Coastal Ecosystems in Puerto Rico (HICE-PR): the Río Loco Watershed (southwest coast PR) project which was funded by NASA is to evaluate the impacts of land use/land cover changes on the quality and extent of coastal and marine ecosystems (CMEs) in two priority watersheds in Puerto Rico (Manatí and Guánica).The main objective of this study is to set up a physically based spatially distributed hydrological model, Soil and Water Assessment Tool (SWAT) for the analysis of hydrological processes in the Rio Grande de Manati river basin. SWAT (soil and water assessment tool) is a spatially distributed watershed model developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds. For efficient use of distributed models for hydrological and scenario analysis, it is important that these models pass through a careful calibration and uncertainty analysis. The model was calibrated and validated using Sequential Uncertainty Fitting (SUFI-2) calibration and uncertainty analysis algorithms. The model evaluation statistics for streamflows prediction shows that there is a good agreement between the measured and simulated flows that was verified by coefficients of determination and Nash Sutcliffe efficiency greater than 0.5. Keywords: Hydrological Modeling; SWAT; SUFI-2; Rio Grande De Manati; Puerto Rico

Decadal-scale relationship between measurements of aerosols, land-use change, and fire over Southeast Asia

NASA Astrophysics Data System (ADS)

Blake Cohen, Jason; Lecoeur, Eve; Loong Ng, Daniel Hui

2017-01-01

A simultaneous analysis of 13 years of remotely sensed data of land cover, fires, precipitation, and aerosols from the MODIS, TRMM, and MISR satellites and the AERONET network over Southeast Asia is performed, leading to a set of robust relationships between land-use change and fire being found on inter-annual and intra-annual scales over Southeast Asia, reflecting the heavy amounts of anthropogenic influence over land-use change and fires in this region of the world. First, we find that fires occur annually, but with a considerable amount of variance in their onset, duration, and intensity from year to year, and from two separate regions within Southeast Asia. Second, we show that a simple regression model of the land-cover, fire, and precipitation data can be used to recreate a robust representation of the timing and magnitude of measured aerosol optical depth (AOD) from multiple measurements sources of this region using either 8-day (better for onset and duration) or monthly (better for magnitude) measurements, but not daily measurements. We find that the reconstructed AOD matches the timing and intensity from AERONET measurements to within 70 to 90 % and the timing and intensity of MISR measurements to within 50 to 95 %. This is a unique finding in this part of the world since cloud-covered regions are large, yet the model is still robustly capable, including over regions where no fires are observed and hence no emissions would be expected to contribute to AOD. Third, we determine that while Southeast Asia is a source region of such intense smoke emissions, portions of it are also impacted by smoke transported from other regions. There are regions in northern Southeast Asia which have two annual AOD peaks, one during the local fire season and the other, smaller peak corresponding to a combination of some local smoke sources as well as transport of aerosols from fires in southern Southeast Asia and possibly even from anthropogenic sources in South Asia. Overall, this study highlights the importance of taking into account a simultaneous use of land-use, fire, and precipitation for understanding the impacts of fires on the atmospheric loading and distribution of aerosols in Southeast Asia over both space and time. Furthermore, it highlights that there are significant advantages of using 8-day and monthly average values (instead of daily data) in order to better quantify the magnitude and timing of Southeast Asia fires.

Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazi

NASA Astrophysics Data System (ADS)

Costa, M. H.; Dias, L. C. P.; Macedo, M.; Coe, M. T.; Neill, C.

2014-12-01

This study assess the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations is improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.

Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazi

NASA Astrophysics Data System (ADS)

Costa, M. H.; Dias, L. C. P.; Macedo, M.; Coe, M. T.; Neill, C.

2015-12-01

This study assess the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations is improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.

Estimation of Land Surface Fluxes and Their Uncertainty via Variational Data Assimilation Approach

NASA Astrophysics Data System (ADS)

Abdolghafoorian, A.; Farhadi, L.

2016-12-01

Accurate estimation of land surface heat and moisture fluxes as well as root zone soil moisture is crucial in various hydrological, meteorological, and agricultural applications. "In situ" measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state variables. In this work, we applied a novel approach based on the variational data assimilation (VDA) methodology to estimate land surface fluxes and soil moisture profile from the land surface states. This study accounts for the strong linkage between terrestrial water and energy cycles by coupling the dual source energy balance equation with the water balance equation through the mass flux of evapotranspiration (ET). Heat diffusion and moisture diffusion into the column of soil are adjoined to the cost function as constraints. This coupling results in more accurate prediction of land surface heat and moisture fluxes and consequently soil moisture at multiple depths with high temporal frequency as required in many hydrological, environmental and agricultural applications. One of the key limitations of VDA technique is its tendency to be ill-posed, meaning that a continuum of possibilities exists for different parameters that produce essentially identical measurement-model misfit errors. On the other hand, the value of heat and moisture flux estimation to decision-making processes is limited if reasonable estimates of the corresponding uncertainty are not provided. In order to address these issues, in this research uncertainty analysis will be performed to estimate the uncertainty of retrieved fluxes and root zone soil moisture. The assimilation algorithm is tested with a series of experiments using a synthetic data set generated by the simultaneous heat and water (SHAW) model. We demonstrate the VDA performance by comparing the (synthetic) true measurements (including profile of soil moisture and temperature, land surface water and heat fluxes, and root water uptake) with VDA estimates. In addition, the feasibility of extending the proposed approach to use remote sensing observations is tested by limiting the number of LST observations and soil moisture observations.

Quantifying the impact of land use change on hydrological responses in the Upper Ganga Basin, India

NASA Astrophysics Data System (ADS)

Tsarouchi, Georgia-Marina; Mijic, Ana; Moulds, Simon; Chawla, Ila; Mujumdar, Pradeep; Buytaert, Wouter

2013-04-01

Quantifying how changes in land use affect the hydrological response at the river basin scale is a challenge in hydrological science and especially in the tropics where many regions are considered data sparse. Earlier work by the authors developed and used high-resolution, reconstructed land cover maps for northern India, based on satellite imagery and historic land-use maps for the years 1984, 1998 and 2010. Large-scale land use changes and their effects on landscape patterns can impact water supply in a watershed by altering hydrological processes such as evaporation, infiltration, surface runoff, groundwater discharge and stream flow. Three land use scenarios were tested to explore the sensitivity of the catchment's response to land use changes: (a) historic land use of 1984 with integrated evolution to 2010; (b) land use of 2010 remaining stable; and (c) hypothetical future projection of land use for 2030. The future scenario was produced with Markov chain analysis and generation of transition probability matrices, indicating transition potentials from one land use class to another. The study used socio-economic (population density), geographic (distances to roads and rivers, and location of protected areas) and biophysical drivers (suitability of soil for agricultural production, slope, aspect, and elevation). The distributed version of the land surface model JULES was integrated at a resolution of 0.01° for the years 1984 to 2030. Based on a sensitivity analysis, the most sensitive parameters were identified. Then, the model was calibrated against measured daily stream flow data. The impact of land use changes was investigated by calculating annual variations in hydrological components, differences in annual stream flow and surface runoff during the simulation period. The land use changes correspond to significant differences on the long-term hydrologic fluxes for each scenario. Once analysed from a future water resources perspective, the results will be beneficial in constructing decision support tools for regional land-use planning and management.

A hybrid HDRF model of GOMS and SAIL: GOSAIL

NASA Astrophysics Data System (ADS)

Dou, B.; Wu, S.; Wen, J.

2016-12-01

Understanding the surface reflectance anisotropy is the key facet in interpreting the features of land surface from remotely sensed information, which describes the property of land surface to reflect the solar radiation directionally. Most reflectance anisotropy models assumed the nature surface was illuminated only by the direct solar radiation, while the diffuse skylight becomes dominant especially for the over cast sky conditions and high rugged terrain. Correcting the effect of diffuse skylight on the reflectance anisotropy to obtain the intrinsic directional reflectance of land surface is highly desirable for remote sensing applications. This paper developed a hybrid HDRF model of GOMS and SAIL called GOSAIL model for discrete canopies. The accurate area proportions of four scene components are calculated by the GOMS model and the spectral signatures of scene components are provided by the SAIL model. Both the single scattering contribution and the multiple scattering contributions within and between the canopy and background under the clear and diffuse illumination conditions are considered in the GOSAIL model. The HDRF simulated by the 3-D Discrete Anisotropic Radiative Transfer (DART) model and the HDRF measurements over the 100m×100m mature pine stand at the Järvselja, Estonia are used for validating and evaluating the performance of proposed GOSAIL model. The comparison results indicate the GOSAIL model can accurately reproducing the angular feature of discrete canopy for both the clear and overcast atmospheric conditions. The GOSAIL model is promising for the land surface biophysical parameters retrieval (e.g. albedo, leaf area index) over the heterogeneous terrain.

Simulation of future land use change and climate change impacts on hydrological processes in a tropical catchment

NASA Astrophysics Data System (ADS)

Marhaento, H.; Booij, M. J.; Hoekstra, A. Y.

2017-12-01

Future hydrological processes in the Samin catchment (278 km2) in Java, Indonesia have been simulated using the Soil and Water Assessment Tool (SWAT) model using inputs from predicted land use distributions in the period 2030 - 2050, bias corrected Regional Climate Model (RCM) output and output of six Global Climate Models (GCMs) to include climate model uncertainty. Two land use change scenarios namely a business-as-usual (BAU) scenario, where no measures are taken to control land use change, and a controlled (CON) scenario, where the future land use follows the land use planning, were used in the simulations together with two climate change scenarios namely Representative Concentration Pathway (RCP) 4.5 and 8.5. It was predicted that in 2050 settlement and agriculture area of the study catchment will increase by 33.9% and 3.5%, respectively under the BAU scenario, whereas agriculture area and evergreen forest will increase by 15.2% and 10.2%, respectively under the CON scenario. In comparison to the baseline conditions (1983 - 2005), the predicted mean annual maximum and minimum temperature in 2030 - 2050 will increase by an average of +10C, while changes in the mean annual rainfall range from -20% to +19% under RCP 4.5 and from -25% to +15% under RCP 8.5. The results show that land use change and climate change individually will cause changes in the water balance components, but that more pronounced changes are expected if the drivers are combined, in particular for changes in annual stream flow and surface runoff. It was observed that combination of the RCP 4.5 climate scenario and BAU land use scenario resulted in an increase of the mean annual stream flow from -7% to +64% and surface runoff from +21% to +102%, which is 40% and 60% more than when land use change is acting alone. Furthermore, under the CON scenario the annual stream flow and surface runoff could be potentially reduced by up to 10% and 30%, respectively indicating the effectiveness of applied land use planning. The findings of this study will be useful for the water resource managers to mitigate future risks associated with land use and climate changes in the study catchment. Keywords: land use change, climate change, hydrological impact assessment, Samin catchment

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

NASA Astrophysics Data System (ADS)

Lin, Y.; Chen, X.

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

The Flora Mission for Ecosystem Composition, Disturbance and Productivity

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Knox, Robert G.; Green, Robert O.; Ungar, Stephen G.

2005-01-01

Global land use and climate variability alter ecosystem conditions - including structure, function, and biological diversity - at a pace that requires unambiguous observations from satellite vantage points. Current global measurements are limited to general land cover, some disturbances, vegetation leaf area index, and canopy energy absorption. Flora is a pathfinding mission that provides new measurements of ecosystem structure, function, and diversity to understand the spatial and temporal dynamics of human and natural disturbances, and the biogeochemical and physiological responses of ecosystems to disturbance. The mission relies upon high-fidelity imaging spectroscopy to deliver full optical spectrum measurements (400-2500 nm) of the global land surface on a monthly time step at 45 meter spatial resolution for three years. The Flora measurement objectives are: (i) fractional cover of biological materials, (ii) canopy water content, (iii) vegetation pigments and light-use efficiency, (iv) plant functional types, (v) fire fuel load and fuel moisture content, and (vi) disturbance occurrence, type and intensity. These measurements are made using a multi-parameter, spectroscopic analysis approach afforded by observation of the full optical spectrum. Combining these measurements, along with additional observations from multispectral sensors, Flora will far advance global studies and models of ecosystem dynamics and change.

Soil erosion by snow gliding - a first quantification attempt in a subalpine area in Switzerland

NASA Astrophysics Data System (ADS)

Meusburger, K.; Leitinger, G.; Mabit, L.; Mueller, M. H.; Walter, A.; Alewell, C.

2014-09-01

Snow processes might be one important driver of soil erosion in Alpine grasslands and thus the unknown variable when erosion modelling is attempted. The aim of this study is to assess the importance of snow gliding as a soil erosion agent for four different land use/land cover types in a subalpine area in Switzerland. We used three different approaches to estimate soil erosion rates: sediment yield measurements in snow glide depositions, the fallout radionuclide 137Cs and modelling with the Revised Universal Soil Loss Equation (RUSLE). RUSLE permits the evaluation of soil loss by water erosion, the 137Cs method integrates soil loss due to all erosion agents involved, and the measurement of snow glide deposition sediment yield can be directly related to snow-glide-induced erosion. Further, cumulative snow glide distance was measured for the sites in the winter of 2009/2010 and modelled for the surrounding area and long-term average winter precipitation (1959-2010) with the spatial snow glide model (SSGM). Measured snow glide distance confirmed the presence of snow gliding and ranged from 2 to 189 cm, with lower values on the north-facing slopes. We observed a reduction of snow glide distance with increasing surface roughness of the vegetation, which is an important information with respect to conservation planning and expected and ongoing land use changes in the Alps. Snow glide erosion estimated from the snow glide depositions was highly variable with values ranging from 0.03 to 22.9 t ha-1 yr-1 in the winter of 2012/2013. For sites affected by snow glide deposition, a mean erosion rate of 8.4 t ha-1 yr-1 was found. The difference in long-term erosion rates determined with RUSLE and 137Cs confirms the constant influence of snow-glide-induced erosion, since a large difference (lower proportion of water erosion compared to total net erosion) was observed for sites with high snow glide rates and vice versa. Moreover, the difference between RUSLE and 137Cs erosion rates was related to the measured snow glide distance (R2 = 0.64; p < 0.005) and to the snow deposition sediment yields (R2 = 0.39; p = 0.13). The SSGM reproduced the relative difference of the measured snow glide values under different land uses and land cover types. The resulting map highlighted the relevance of snow gliding for large parts of the investigated area. Based on these results, we conclude that snow gliding appears to be a crucial and non-negligible process impacting soil erosion patterns and magnitude in subalpine areas with similar topographic and climatic conditions.

Definition of different land uses and their effects on farmers income and soil sustainability using monte carlo simulations

NASA Astrophysics Data System (ADS)

Stolte, J.; Ritsema, C. J.; Bouma, J.

2003-04-01

On the Loess Plateau in China, soil erosion amounts to between 10 000 and 25 000 tons/km^2 per year. The Chinese government acknowledges the erosion problem and promotes comprehensive erosion control. Erosion modeling might be a useful tool to understand and predict erosion and to ultimately find ways to prevent it. There is a growing awareness that successful research will have to take into account the farmers' objectives and constraints, and that it can benefit from their knowledge of local conditions. Erosion modeling as a tool in quantifying effects of alternative land uses requires knowledge of local biophysical parameters. Spatial and temporal variability of soil hydraulic conductivity are important parameters in soil erosion studies. A detailed investigation on the heterogeneity of the saturated conductivity and the implications for model outcome has to be carried out. The integrated goal of this study was to investigate the effect of different land use scenarios, based upon physical, economical and farmers points of view, on discharge and sediment losses, using stochastical distributions of measured field K_s values. The study area (Danangou catchment) is located in the middle part of the Loess Plateau in the northern part of Shaanxi Province. The catchment is about 3.5 km^2 in size, and drains directly into the Yanhe river. The elevation of the catchment ranges from 1085 to 1370 m above sea level. In the catchment, two villages, Leipingta and Danangou, are situated. In 1998, the total population in the catchment was 206 individuals belonging to 46 households. Average land area per household was about 1-2 ha, including small-scattered field plots. In this study, four land-use scenarios are identified: (i) current situation; (ii) an agricultural driven scenario; (iii) participatory planning-driven scenario; (iv) a soil physical driven scenario. In this study, the physically based hydrological and soil erosion model is used to quantify effects of land use on discharge and soil loss. To compare the effects of the defined land use scenarios, calculations were performed using a single rain event. For the saturated conductivity values, use was made of the geometric mean of the measured values for identified land-use groups. By randomly assigning values to each calculation grid-cell, a more diverse outcome of the model is expected reflecting the reality in a more credible way. To achieve this, for each land use scenario 50 drawings of the set of K_s values were performed. The participatory planning-driven scenario proved to produce minimal discharge, while under the current land use the discharge is high. All model outcome parameters showed higher values using the average value of K_s in comparison with the the use of stochastic values of K_s. By using stochastic values of K_s, confidence intervals of model outcome are introduced that reflect the uncertainty in input values and produce more realistic model outcome in terms of confidentiality and acceptability. Alternative land use will have a direct influence on the income of the farmers in the Danangou catchment. In the Participatory Conservation Planning a Participatory Household Economy Analysis (PHEA method) was developed to predict potential changes in household economy. The changes in farm production due to converting land as a result of different scenarios, was calculated in this study based on the results of the PHEA. The agricultural driven scenario resulted in a decrease of cropland, whereas the income increased. This indicates that when effort is put in extension work, the crop production (and therefor the income of the local people) can increase, without negative effects on discharge and soil erosion. The participatory planning-driven scenario, which extracts most of the cropland to be used for production, showed a considerable decrease in income.

Characterizing bidirectional reflectance and spectral albedo of various land cover types in Midwest using GeoTASO Summer-2014 campaign

NASA Astrophysics Data System (ADS)

Wulamu, A.; Fishman, J.; Maimaitiyiming, M.; Leitch, J. W.; Zoogman, P.; Liu, X.; Chance, K.; Marshall, B.

2015-12-01

Understanding the bi-directional reflectance function (BRDF) and spectral albedo of various land-cover types is critical for retrieval of trace gas measurements from planned geostationary satellites such as the Tropospheric Emissions: Monitoring of Pollution (TEMPO). Radiant energy, which will be measured by these instruments at the top of atmosphere (TOA) at unprecedented spectral resolution, is strongly influenced by how this energy is reflected by the underlying surface. Thus, it is critical that we understand this phenomenon at comparable wavelength resolution. As part of the NASA ESTO-funded Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) development project, we carried out synchronous field and airborne data collection campaigns in the St Louis Metro region in Summer 2014. We collected spectral reflectance data of various land cover types on the ground within hours of a GeoTASO overpass using a field-based hyperspectral spectroradiometer (model PSR3500 from Spectral Evolution). Field measurements collecting in-situ spectral albedo and bidirectional reflectance factors were also obtained in July and August of 2015. In this study, we present our preliminary findings from in-situ and airborne GeoTASO derived spectral albedo and BRDF characteristics of major land cover types at TEMPO spectral profiles, which are necessary for the accurate retrieval of tropospheric trace gases and aerosols. First, a spectral database of various targets (e.g., plants, soils, rocks, man-made objects and water) was developed using field measurements. Next, the GeoTASO airborne data were corrected using MODTRAN and field measurements to derive spectral albedo and BRDF. High spatial resolution land-cover types were extracted using satellite images (e.g., Landsat, WorldView, IKONOS, etc.) at resolutions from 2 m - 30 m. Lastly, spectral albedo/BRDFs corresponding to various land cover types were analyzed using both field and GeoTASO measurements.

Assessing biodiversity loss due to land use with Life Cycle Assessment: are we there yet?

PubMed

Souza, Danielle M; Teixeira, Ricardo F M; Ostermann, Ole P

2015-01-01

Ecosystems are under increasing pressure from human activities, with land use and land-use change at the forefront of the drivers that provoke global and regional biodiversity loss. The first step in addressing the challenge of how to reverse the negative outlook for the coming years starts with measuring environmental loss rates and assigning responsibilities. Pinpointing the global pressures on biodiversity is a task best addressed using holistic models such as Life Cycle Assessment (LCA). LCA is the leading method for calculating cradle-to-grave environmental impacts of products and services; it is actively promoted by many public policies, and integrated as part of environmental information systems within private companies. LCA already deals with the potential biodiversity impacts of land use, but there are significant obstacles to overcome before its models grasp the full reach of the phenomena involved. In this review, we discuss some pressing issues that need to be addressed. LCA mainly introduces biodiversity as an endpoint category modeled as a loss in species richness due to the conversion and use of land over time and space. The functional and population effects on biodiversity are mostly absent due to the emphasis on species accumulation with limited geographic and taxonomical reach. Current land-use modeling activities that use biodiversity indicators tend to oversimplify the real dynamics and complexity of the interactions of species among each other and with their habitats. To identify the main areas for improvement, we systematically reviewed LCA studies on land use that had findings related to global change and conservation ecology. We provide suggestion as to how to address some of the issues raised. Our overall objective was to encourage companies to monitor and take concrete steps to address the impacts of land use on biodiversity on a broader geographical scale and along increasingly globalized supply chains. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Incorporating Sentinel-2-like remote sensing products in the hydrometeorological modelling over an agricultural area in south west France

NASA Astrophysics Data System (ADS)

Rivalland, Vincent; Gascoin, Simon; Etchanchu, Jordi; Coustau, Mathieu; Cros, Jérôme; Tallec, Tiphaine

2016-04-01

The Sentinel-2 mission will enable to monitor the land cover and the vegetation phenology at high-resolution (HR) every 5 days. However, current Land Surface Models (LSM) typically use land cover and vegetation parameters derived from previous low to mid resolution satellite missions. Here we studied the effect of introducing Sentinel-2-like data in the simulation of the land surface energy and water fluxes in a region dominated by cropland. Simulations were performed with the ISBA-SURFEX LSM, which is used in the operational hydrometeorological chain of Meteo-France for hydrological forecasts and drought monitoring. By default, SURFEX vegetation land surface parameters and temporal evolution are from the ECOCLIMAP II European database mostly derived from MODIS products at 1 km resolution. The model was applied to an experimental area of 30 km by 30 km in south west France. In this area the resolution of ECOCLIMAP is coarser than the typical size of a crop field. This means that several crop types can be mixed in a pixel. In addition ECOCLIMAP provides a climatology of the vegetation phenology and thus does not account for the interannual effects of the climate and land management on the crop growth. In this work, we used a series of 26 Formosat-2 images at 8-m resolution acquired in 2006. From this dataset, we derived a land cover map and a leaf area index map (LAI) at each date, which were substituted to the ECOCLIMAP land cover map and the LAI maps. The model output water and energy fluxes were compared to a standard simulation using ECOCLIMAP only and to in situ measurements of soil moisture, latent and sensible heat fluxes. The results show that the introduction of the HR products improved the timing of the evapotranspiration. The impact was the most visible on the crops having a growing season in summer (maize, sunflower), because the growth period is more sensitive to the climate.

Assessing biodiversity loss due to land use with Life Cycle Assessment: are we there yet?

PubMed Central

Souza, Danielle M; Teixeira, Ricardo FM; Ostermann, Ole P

2015-01-01

Ecosystems are under increasing pressure from human activities, with land use and land-use change at the forefront of the drivers that provoke global and regional biodiversity loss. The first step in addressing the challenge of how to reverse the negative outlook for the coming years starts with measuring environmental loss rates and assigning responsibilities. Pinpointing the global pressures on biodiversity is a task best addressed using holistic models such as Life Cycle Assessment (LCA). LCA is the leading method for calculating cradle-to-grave environmental impacts of products and services; it is actively promoted by many public policies, and integrated as part of environmental information systems within private companies. LCA already deals with the potential biodiversity impacts of land use, but there are significant obstacles to overcome before its models grasp the full reach of the phenomena involved. In this review, we discuss some pressing issues that need to be addressed. LCA mainly introduces biodiversity as an endpoint category modeled as a loss in species richness due to the conversion and use of land over time and space. The functional and population effects on biodiversity are mostly absent due to the emphasis on species accumulation with limited geographic and taxonomical reach. Current land-use modeling activities that use biodiversity indicators tend to oversimplify the real dynamics and complexity of the interactions of species among each other and with their habitats. To identify the main areas for improvement, we systematically reviewed LCA studies on land use that had findings related to global change and conservation ecology. We provide suggestion as to how to address some of the issues raised. Our overall objective was to encourage companies to monitor and take concrete steps to address the impacts of land use on biodiversity on a broader geographical scale and along increasingly globalized supply chains. PMID:25143302

Carbon fluxes in a heterogeneous estuarine wetland in Northern Ohio. Comparing eddy covariance and chamber measurements

NASA Astrophysics Data System (ADS)

Rey Sanchez, C.; Morin, T. H.; Stefanik, K. C.; Wrighton, K. C.; Bohrer, G.

2016-12-01

Wetlands are important carbon dioxide (CO2) sinks but also the largest source of methane (CH4), a powerful greenhouse gas. Wetlands are often heterogeneous landscapes with highly diverse land covers and different paths of CH4 release and CO2 uptake. Understanding the ecosystem level greenhouse gas budget of a wetland involves understanding several carbon fluxes associated with each of the different land cover patches. We studied CO2 and CH4 fluxes from different land cover types at the Old Woman Creek (OWC) National Estuarine Research Reserve, at the Lake Erie shore in Northern Ohio. OWC is composed of four main types of land cover: open water, emergent cattail vegetation (Typha spp), floating vegetation (Nelimbo spp), and mud flats. CH4 and CO2 gas exchange was measured in each patch type using enclosed chambers monthly during the growing seasons of 2015 and 2016. During the same period of time, an eddy covariance tower was deployed in a representative section of the wetland to measure continuous site-level CO2 and CH4 fluxes. A footprint model was used to account for the relative contributions of each patch type to the flux measured by the tower. The chamber measurements were used to constrain the contributions of each patch within the flux tower footprint, and to correct the flux measurements to the whole-wetland total flux. We analyzed the spatial and temporal variability of methane and carbon dioxide and related this variation to some of the most important environmental drivers at the site. We used these data to analyze the implications of different arrangements of land cover types on the carbon balance and greenhouse-gas budget in wetlands.

Global and local indicators of spatial association between points and polygons: A study of land use change

NASA Astrophysics Data System (ADS)

Guo, Luo; Du, Shihong; Haining, Robert; Zhang, Lianjun

2013-04-01

The existing indicators related to spatial association, especially the K function, can measure only the same dimension of vector data, such as points, lines and polygons, respectively. We develop four new indicators that can analyze and model spatial association for the mixture of different dimensions of vector data, such as lines and points, points and polygons, lines and polygons. The four indicators can measure the spatial association between points and polygons from both global and local perspectives. We also apply the presented methods to investigate the association of temples and villages on land-use change at multiple distance scales in the Guoluo Tibetan Autonomous Prefecture in Qinghai Province, PR China. Global indicators show that temples are positively associated with land-use change at large spatial distances (e.g., >6000 m), while the association between villages and land-use change is insignificant at all distance scales. Thus temples, as religious and cultural centers, have a stronger association with land-use change than the places where people live. However, local indicators show that these associations vary significantly in different sub-areas of the study region. Furthermore, the association of temples with land-use change is also dependent on the specific type of land-use change. The case study demonstrates that the presented indicators are powerful tools for analyzing the spatial association between points and polygons.

Remote sensing of land use and water quality relationships - Wisconsin shore, Lake Michigan

NASA Technical Reports Server (NTRS)

Haugen, R. K.; Marlar, T. L.

1976-01-01

This investigation assessed the utility of remote sensing techniques in the study of land use-water quality relationships in an east central Wisconsin test area. The following types of aerial imagery were evaluated: high altitude (60,000 ft) color, color infrared, multispectral black and white, and thermal; low altitude (less than 5000 ft) color infrared, multispectral black and white, thermal, and passive microwave. A non-imaging hand-held four-band radiometer was evaluated for utility in providing data on suspended sediment concentrations. Land use analysis includes the development of mapping and quantification methods to obtain baseline data for comparison to water quality variables. Suspended sediment loads in streams, determined from water samples, were related to land use differences and soil types in three major watersheds. A multiple correlation coefficient R of 0.85 was obtained for the relationship between the 0.6-0.7 micrometer incident and reflected radiation data from the hand-held radiometer and concurrent ground measurements of suspended solids in streams. Applications of the methods and baseline data developed in this investigation include: mapping and quantification of land use; input to watershed runoff models; estimation of effects of land use changes on stream sedimentation; and remote sensing of suspended sediment content of streams. High altitude color infrared imagery was found to be the most acceptable remote sensing technique for the mapping and measurement of land use types.

Artificialized land characteristics and sediment connectivity explain muddy flood hazard in Wallonia

NASA Astrophysics Data System (ADS)

de Walque, Baptiste; Bielders, Charles; Degré, Aurore; Maugnard, Alexandre

2017-04-01

Muddy flood occurrence is an off-site erosion problem of growing interest in Europe and in particular in the loess belt and Condroz regions of Wallonia (Belgium). In order to assess the probability of occurrence of muddy floods in specific places, a muddy flood hazard prediction model has been built. It was used to test 11 different explanatory variables in simple and multiple logistic regressions approaches. A database of 442 muddy flood-affected sites and an equal number of homologous non flooded sites was used. For each site, relief, land use, sediment production and sediment connectivity of the contributing area were extracted. To assess the prediction quality of the model, we proceeded to a validation using 48 new pairs of homologous sites. Based on Akaïke Information Criterion (AIC), we determined that the best muddy flood hazard assessment model requires a total of 6 explanatory variable as inputs: the spatial aggregation of the artificialized land, the sediment connectivity, the artificialized land proximity to the outlet, the proportion of artificialized land, the mean slope and the Gravelius index of compactness of the contributive area. The artificialized land properties listed above showed to improve substantially the model quality (p-values from 10e-10 to 10e-4). All of the 3 properties showed negative correlation with the muddy flood hazard. These results highlight the importance of considering the artificialized land characteristics in the sediment transport assessment models. Indeed, artificialized land such as roads may dramatically deviate flows and influence the connectivity in the landscape. Besides the artificialized land properties, the sediment connectivity showed significant explanatory power (p-value of 10e-11). A positive correlation between the sediment connectivity and the muddy flood hazard was found, ranging from 0.3 to 0.45 depending on the sediment connectivity index. Several studies already have highlighted the importance of this parameter in the sediment transport characterization in the landscape. Using the best muddy flood probability of occurrence threshold value of 0.49, the validation of the best multiple logistic regression resulted in a prediction quality of 75.6% (original dataset) and 81.2% (secondary dataset). The developed statistical model could be used as a reliable tool to target muddy floods mitigation measures in sites resulting with the highest muddy floods hazard.

Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions

NASA Astrophysics Data System (ADS)

Serafimovich, Andrei; Metzger, Stefan; Hartmann, Jörg; Kohnert, Katrin; Zona, Donatella; Sachs, Torsten

2018-03-01

The objective of this study was to upscale airborne flux measurements of sensible heat and latent heat and to develop high resolution flux maps. In order to support the evaluation of coupled atmospheric/land-surface models we investigated spatial patterns of energy fluxes in relation to land-surface properties. We used airborne eddy-covariance measurements acquired by the POLAR 5 research aircraft in June-July 2012 to analyze surface fluxes. Footprint-weighted surface properties were then related to 21 529 sensible heat flux observations and 25 608 latent heat flux observations using both remote sensing and modelled data. A boosted regression tree technique was used to estimate environmental response functions between spatially and temporally resolved flux observations and corresponding biophysical and meteorological drivers. In order to improve the spatial coverage and spatial representativeness of energy fluxes we used relationships extracted across heterogeneous Arctic landscapes to infer high-resolution surface energy flux maps, thus directly upscaling the observational data. These maps of projected sensible heat and latent heat fluxes were used to assess energy partitioning in northern ecosystems and to determine the dominant energy exchange processes in permafrost areas. This allowed us to estimate energy fluxes for specific types of land cover, taking into account meteorological conditions. Airborne and modelled fluxes were then compared with measurements from an eddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependent quantification of surface energy fluxes and provide new insights into the processes affecting these fluxes for the main vegetation types in high-latitude permafrost areas.

Constitutive Soil Properties for Mason Sand and Kennedy Space Center

NASA Technical Reports Server (NTRS)

Thomas, Michael A.; Chitty, Daniel E.

2011-01-01

Accurate soil models are required for numerical simulations of land landings for the Orion Crew Exploration Vehicle (CEV). This report provides constitutive material models for two soil conditions at Kennedy Space Center (KSC) and four conditions of Mason Sand. The Mason Sand is the test sand for LaRC s drop tests and swing tests of the Orion. The soil models are based on mechanical and compressive behavior observed during geotechnical laboratory testing of remolded soil samples. The test specimens were reconstituted to measured in situ density and moisture content. Tests included: triaxial compression, hydrostatic compression, and uniaxial strain. A fit to the triaxial test results defines the strength envelope. Hydrostatic and uniaxial tests define the compressibility. The constitutive properties are presented in the format of LSDYNA Material Model 5: Soil and Foam. However, the laboratory test data provided can be used to construct other material models. The soil models are intended to be specific to the soil conditions they were tested at. The two KSC models represent two conditions at KSC: low density dry sand and high density in-situ moisture sand. The Mason Sand model was tested at four conditions which encompass measured conditions at LaRC s drop test site.

Integrating spatially explicit representations of landscape perceptions into land change research

USGS Publications Warehouse

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

2017-01-01

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

Hydrological Responses of Climate and Land Use/Cover Changes in Tao'er River Basin Based on the SWAT Model

NASA Astrophysics Data System (ADS)

Liu, J.; Kou, L.

2015-12-01

Abstract: The changes of both climate and land use/cover have some impact on the water resources. For Tao'er River Basin, these changes have a direct impact on the land use pattern adjustment, wetland protection, connection project between rivers and reservoirs, local social and economic development, etc. Therefore, studying the impact of climate and land use/cover changes is of great practical significance. The Soil and Water Assessment Tool (SWAT) is used as the research method. With historical actual measured runoff data and the yearly land use classification caught by satellite remote sensing maps, analyze the impact of climate change on the runoff of Tao'er River. And according to the land use/cover classification of 1990, 2000 and 2010, analyze the land use/cover change in the recent 30 years, the impact of the land use/cover change on the river runoff and the contribution coefficient of farmland, woodland, grassland and other major land-use types to the runoff. These studies can provide some references to the rational allocation of water resource and adjustment of land use structure in this area.

Spatial scale of land-use impacts on riverine drinking source water quality

NASA Astrophysics Data System (ADS)

Hurley, Tim; Mazumder, Asit

2013-03-01

Drinking water purveyors are increasingly relying on land conservation and management to ensure the safety of the water that they provide to consumers. To cost-effectively implement any such landscape initiatives, resources must be targeted to the appropriate spatial scale to address quality impairments of concern in a cost-effective manner. Using data gathered from 40 Canadian rivers across four ecozones, we examined the spatial scales at which land use was most closely associated with drinking source water quality metrics. Exploratory linear mixed-effects models accounting for climatic, hydrological, and physiographic variation among sites suggested that different spatial areas of land-use influence drinking source water quality depending on the parameter and season investigated. Escherichia coli spatial variability was only associated with land use at a local (5-10 km) spatial scale. Turbidity measures exhibited a complex association with land use, suggesting that the land-use areas of greatest influence can range from a 1 km subcatchment to the entire watershed depending on the season. Total organic carbon concentrations were only associated with land use characterized at the entire watershed scale. The Canadian Council of Ministers of the Environment Water Quality Index was used to calculate a composite measure of seasonal drinking source water quality but did not provide additional information beyond the analyses of individual parameters. These results suggest that entire watershed management is required to safeguard drinking water sources with more focused efforts at targeted spatial scales to reduce specific risk parameters.

Rock Statistics at the Mars Pathfinder Landing Site, Roughness and Roving on Mars

NASA Technical Reports Server (NTRS)

Haldemann, A. F. C.; Bridges, N. T.; Anderson, R. C.; Golombek, M. P.

1999-01-01

Several rock counts have been carried out at the Mars Pathfinder landing site producing consistent statistics of rock coverage and size-frequency distributions. These rock statistics provide a primary element of "ground truth" for anchoring remote sensing information used to pick the Pathfinder, and future, landing sites. The observed rock population statistics should also be consistent with the emplacement and alteration processes postulated to govern the landing site landscape. The rock population databases can however be used in ways that go beyond the calculation of cumulative number and cumulative area distributions versus rock diameter and height. Since the spatial parameters measured to characterize each rock are determined with stereo image pairs, the rock database serves as a subset of the full landing site digital terrain model (DTM). Insofar as a rock count can be carried out in a speedier, albeit coarser, manner than the full DTM analysis, rock counting offers several operational and scientific products in the near term. Quantitative rock mapping adds further information to the geomorphic study of the landing site, and can also be used for rover traverse planning. Statistical analysis of the surface roughness using the rock count proxy DTM is sufficiently accurate when compared to the full DTM to compare with radar remote sensing roughness measures, and with rover traverse profiles.

Changes in Fatigue, Multiplanar Knee Laxity, and Landing Biomechanics During Intermittent Exercise

PubMed Central

Shultz, Sandra J.; Schmitz, Randy J.; Cone, John R.; Henson, Robert A.; Montgomery, Melissa M.; Pye, Michele L.; Tritsch, Amanda J.

2015-01-01

Context: Knee laxity increases during exercise. However, no one, to our knowledge, has examined whether these increases contribute to higher-risk landing biomechanics during prolonged, fatiguing exercise. Objectives: To examine associations between changes in fatigue (measured as sprint time [SPTIME]), multiplanar knee laxity (anterior-posterior [APLAX], varus-valgus [VVLAX] knee laxity, and internal-external rotation [IERLAX]) knee laxity and landing biomechanics during prolonged, intermittent exercise. Design: Descriptive laboratory study. Setting: Laboratory and gymnasium. Patients or Other Participants: A total of 30 male (age = 20.3 ± 2.0 years, height = 1.79 ± 0.05 m, mass = 75.2 ± 7.2 kg) and 29 female (age = 20.5 ± 2.3 years, height = 1.67 ± 0.08 m, mass = 61.8 ± 9.0 kg) competitive athletes. Intervention(s): A 90-minute intermittent exercise protocol (IEP) designed to simulate the physiologic and biomechanical demands of a soccer match. Main Outcome Measure(s): We measured SPTIME, APLAX, and landing biomechanics before and after warm-up, every 15 minutes during the IEP, and every 15 minutes for 1 hour after the IEP. We measured VVLAX and IERLAX before and after the warm-up, at 45 and 90 minutes during the IEP, and at 30 minutes after the IEP. We used hierarchical linear modeling to examine associations between exercise-related changes in SPTIME and knee laxity with exercise-related changes in landing biomechanics while controlling for initial (before warm-up) knee laxity. Results: We found that SPTIME had a more global effect on landing biomechanics in women than in men, resulting in a more upright landing and a reduction in landing forces and out-of-plane motions about the knee. As APLAX increased with exercise, women increased their knee internal-rotation motion (P = .02), and men increased their hip-flexion motion and energy-absorption (P = .006) and knee-extensor loads (P = .04). As VVLAX and IERLAX increased, women went through greater knee-valgus motion and dorsiflexion and absorbed more energy at the knee (P ≤ .05), whereas men were positioned in greater hip external and knee internal rotation and knee valgus throughout the landing (P = .03). The observed fatigue- and laxity-related changes in landing biomechanics during exercise often depended on initial knee laxity. Conclusions: Both exercise-related changes in fatigue and knee laxity were associated with higher-risk landing biomechanics during prolonged exercise. These relationships were more pronounced in participants with greater initial knee laxity. PMID:25674926

Inverting Comet Acoustic Surface Sounding Experiment (CASSE) touchdown signals to measure the elastic modulus of comet material

NASA Astrophysics Data System (ADS)

Arnold, W.; Faber, C.; Knapmeyer, M.; Witte, L.; Schröder, S.; Tune, J.; Möhlmann, D.; Roll, R.; Chares, B.; Fischer, H.; Seidensticker, K.

2014-07-01

The landing of Philae on comet 67P/Churyumov-Gerasimenko is scheduled for November 11, 2014. Each of the three landing feet of Philae house a triaxial acceleration sensor of CASSE, which will thus be the first sensors to be in mechanical contact with the cometary surface. CASSE will be in listening mode to record the deceleration of the lander, when it impacts with the comet at a velocity of approx. 0.5 m/s. The analysis of this data yields information on the reduced elastic modulus and the yield stress of the comet's surface material. We describe a series of controlled landings of a lander model. The tests were conducted in the Landing & Mobility Test Facility (LAMA) of the DLR Institute of Space Systems in Bremen, Germany, where an industrial robot can be programmed to move landers or rovers along predefined paths, allowing to adapt landing procedures with predefined velocities. The qualification model of the Philae landing gear was used in the tests. It consists of three legs manufactured of carbon fiber and metal joints. A dead mass of the size and mass of the lander housing is attached via a damper above the landing gear to represent the lander structure as a whole. Attached to each leg is a foot with two soles and a mechanically driven fixation screw (''ice screw'') to secure the lander on the comet. The right soles, if viewed from the outside towards the lander body, house a Brüel & Kjaer DeltaTron 4506 triaxial piezoelectric accelerometer as used on the spacecraft. Orientation of the three axes was such that one of the axes, here the X-axis of the accelerometer, points downwards, while the Y- and Z-axes are horizontal. Data were recorded at a sampling rate of 8.2 kHz within a time gate of 2 s. In parallel, a video sequence was taken, in order to monitor the touchdown on the sand and the movement of the ice screws. Touchdown measurements were conducted on three types of ground with landing velocities between 0.1 to 1.1 m/s. Landings with low velocities were carried out on the concrete floor of the LAMA to determine the stiffness of the landing gear based on the deceleration data measured with the accelerometer. Landings on fine-grained quartz sand and on a Mars soil simulant (brand names WF34 and MSS-D, respectively) allow quantifying the changes of the deceleration data due to interaction with the soil. The elastic moduli of the soils that were inverted from the accelerometer data agree well with data obtained by ultrasonic time-of-flight measurements, provided an effective contact area is used. To this end, the lander structure was viewed in a simplified way as a mass-spring-damper system coupled to the soil by a contact spring, whose stiffness is determined by elastic moduli of the soil and the contact radius. Analytical expressions allow a rapid inversion of the deceleration data to obtain elastic data. It is expected that the same procedure can be applied to the signal measured when landing on comet 67P.

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.

Development of European NO2 Land Use Regression Model for present and future exposure assessment: Implications for policy analysis.

PubMed

Vizcaino, Pilar; Lavalle, Carlo

2018-05-04

A new Land Use Regression model was built to develop pan-European 100 m resolution maps of NO 2 concentrations. The model was built using NO 2 concentrations from routine monitoring stations available in the Airbase database as dependent variable. Predictor variables included land use, road traffic proxies, population density, climatic and topographical variables, and distance to sea. In order to capture international and inter regional disparities not accounted for with the mentioned predictor variables, additional proxies of NO 2 concentrations, like levels of activity intensity and NO x emissions for specific sectors, were also included. The model was built using Random Forest techniques. Model performance was relatively good given the EU-wide scale (R 2  = 0.53). Output predictions of annual average concentrations of NO 2 were in line with other existing models in terms of spatial distribution and values of concentration. The model was validated for year 2015, comparing model predictions derived from updated values of independent variables, with concentrations in monitoring stations for that year. The algorithm was then used to model future concentrations up to the year 2030, considering different emission scenarios as well as changes in land use, population distribution and economic factors assuming the most likely socio-economic trends. Levels of exposure were derived from maps of concentration. The model proved to be a useful tool for the ex-ante evaluation of specific air pollution mitigation measures, and more broadly, for impact assessment of EU policies on territorial development. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Modelling past land use using archaeological and pollen data

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Assessing the Regional/Diurnal Bias between Satellite Retrievals and GEOS-5/MERRA Model Estimates of Land Surface Temperature

NASA Astrophysics Data System (ADS)

Scarino, B. R.; Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.

2017-12-01

Atmospheric models rely on high-accuracy, high-resolution initial radiometric and surface conditions for better short-term meteorological forecasts, as well as improved evaluation of global climate models. Continuous remote sensing of the Earth's energy budget, as conducted by the Clouds and Earth's Radiant Energy System (CERES) project, allows for near-realtime evaluation of cloud and surface radiation properties. It is unfortunately common for there to be bias between atmospheric/surface radiation models and Earth-observations. For example, satellite-observed surface skin temperature (Ts), an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface, can be biased due to atmospheric adjustment assumptions and anisotropy effects. Similarly, models are potentially biased by errors in initial conditions and regional forcing assumptions, which can be mitigated through assimilation with true measurements. As such, when frequent, broad-coverage, and accurate retrievals of satellite Ts are available, important insights into model estimates of Ts can be gained. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared method to produce anisotropy-corrected Ts over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) satellite imagers. Regional and diurnal changes in model land surface temperature (LST) performance can be assessed owing to the somewhat continuous measurements of the LST offered by GEO satellites - measurements which are accurate to within 0.2 K. A seasonal, hourly comparison of satellite-observed LST with the NASA Goddard Earth Observing System Version 5 (GEOS-5) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA) LST estimates is conducted to reveal regional and diurnal biases. This assessment is an important first step for evaluating the effectiveness of Ts assimilation, as well for determining the impact anisotropy correction has on observation - model bias, and is of critical importance for CERES.

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.

Static Footprint Local Forces, Areas, and Aspect Ratios for Three Type 7 Aircraft Tires

NASA Technical Reports Server (NTRS)

Howell, William E.; Perez, Sharon E.; Vogler, William A.

1991-01-01

The National Tire Modeling Program (NTMP) is a joint NASA/industry effort to improve the understanding of tire mechanics and develop accurate analytical design tools. This effort includes fundamental analytical and experimental research on the structural mechanics of tires. Footprint local forces, areas, and aspect ratios were measured. Local footprint forces in the vertical, lateral, and drag directions were measured with a special footprint force transducer. Measurements of the local forces in the footprint were obtained by positioning the transducer at specified locations within the footprint and externally loading the tires. Three tires were tested: (1) one representative of those used on the main landing gear of B-737 and DC-9 commercial transport airplanes, (2) a nose landing gear tire for the Space Shuttle Orbiter, and (3) a main landing gear tire for the Space Shuttle Orbiter. Data obtained for various inflation pressures and vertical loads are presented for two aircraft tires. The results are presented in graphical and tabulated forms.

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.

Evaluation of terrestrial carbon cycle models with atmospheric CO2 measurements: Results from transient simulations considering increasing CO2, climate, and land-use effects

USGS Publications Warehouse

Dargaville, R.J.; Heimann, Martin; McGuire, A.D.; Prentice, I.C.; Kicklighter, D.W.; Joos, F.; Clein, Joy S.; Esser, G.; Foley, J.; Kaplan, J.; Meier, R.A.; Melillo, J.M.; Moore, B.; Ramankutty, N.; Reichenau, T.; Schloss, A.; Sitch, S.; Tian, H.; Williams, L.J.; Wittenberg, U.

2002-01-01

An atmospheric transport model and observations of atmospheric CO2 are used to evaluate the performance of four Terrestrial Carbon Models (TCMs) in simulating the seasonal dynamics and interannual variability of atmospheric CO2 between 1980 and 1991. The TCMs were forced with time varying atmospheric CO2 concentrations, climate, and land use to simulate the net exchange of carbon between the terrestrial biosphere and the atmosphere. The monthly surface CO2 fluxes from the TCMs were used to drive the Model of Atmospheric Transport and Chemistry and the simulated seasonal cycles and concentration anomalies are compared with observations from several stations in the CMDL network. The TCMs underestimate the amplitude of the seasonal cycle and tend to simulate too early an uptake of CO2 during the spring by approximately one to two months. The model fluxes show an increase in amplitude as a result of land-use change, but that pattern is not so evident in the simulated atmospheric amplitudes, and the different models suggest different causes for the amplitude increase (i.e., CO2 fertilization, climate variability or land use change). The comparison of the modeled concentration anomalies with the observed anomalies indicates that either the TCMs underestimate interannual variability in the exchange of CO2 between the terrestrial biosphere and the atmosphere, or that either the variability in the ocean fluxes or the atmospheric transport may be key factors in the atmospheric interannual variability.

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

Prediction of sedimentation using integration of RS, RUSLE model and GIS in Cameron Highlands, Pahang, Malaysia

NASA Astrophysics Data System (ADS)

Ghani, A. H. A.; Lihan, T.; Rahim, S. A.; Musthapha, M. A.; Idris, W. M. R.; Rahman, Z. A.

2013-11-01

Soil erosion and sediment yield are strongly affected by land use change. Spatially distributed erosion models are of great interest to predict soil erosion loss and sediment yield. Hence, the objective of this study was to determine sediment yield using Revised Universal Soil Loss Equation (RUSLE) model in Geographical Information System (GIS) environment at Cameron Highlands, Pahang, Malaysia. Sediment yield at the study area was determined using RUSLE model in GIS environment The RUSLE factors were computed by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using soil map and field measurement, vegetation cover (C) using satellite images, length and steepness (LS) using contour map and conservation practices using satellite images based on land use/land cover. Field observations were also done to verify the predicted sediment yield. The results indicated that the rate of sediment yield in the study area ranged from very low to extremely high. The higher SY value can be found at middle and lower catchments of Cameron Highland. Meanwhile, the lower SY value can be found at the north part of the study area. Sediment yield value turned out to be higher close to the river due to the topographic characteristic, vegetation type and density, climate and land use within the drainage basin.

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

A Model-based Approach to Scaling GPP and NPP in Support of MODIS Land Product Validation

NASA Astrophysics Data System (ADS)

Turner, D. P.; Cohen, W. B.; Gower, S. T.; Ritts, W. D.

2003-12-01

Global products from the Earth-orbiting MODIS sensor include land cover, leaf area index (LAI), FPAR, 8-day gross primary production (GPP), and annual net primary production (NPP) at the 1 km spatial resolution. The BigFoot Project was designed specifically to validate MODIS land products, and has initiated ground measurements at 9 sites representing a wide array of vegetation types. An ecosystem process model (Biome-BGC) is used to generate estimates of GPP and NPP for each 5 km x 5 km BigFoot site. Model inputs include land cover and LAI (from Landsat ETM+), daily meteorological data (from a centrally located eddy covariance flux tower), and soil characteristics. Model derived outputs are validated against field-measured NPP and flux tower-derived GPP. The resulting GPP and NPP estimates are then aggregated to the 1 km resolution for direct spatial comparison with corresponding MODIS products. At the high latitude sites (tundra and boreal forest), the MODIS GPP phenology closely tracks the BigFoot GPP, but there is a high bias in the MODIS GPP. In the temperate zone sites, problems with the timing and magnitude of the MODIS FPAR introduce differences in MODIS GPP compared to the validation data at some sites. However, the MODIS LAI/FPAR data are currently being reprocessed (=Collection 4) and new comparisons will be made for 2002. The BigFoot scaling approach permits precise overlap in spatial and temporal resolution between the MODIS products and BigFoot products, and thus permits the evaluation of specific components of the MODIS NPP algorithm. These components include meteorological inputs from the NASA Data Assimilation Office, LAI and FPAR from other MODIS algorithms, and biome-specific parameters for base respiration rate and light use efficiency.

A Physical Model to Estimate Snowfall over Land using AMSU-B Observations

NASA Technical Reports Server (NTRS)

Kim, Min-Jeong; Weinman, J. A.; Olson, W. S.; Chang, D.-E.; Skofronick-Jackson, G.; Wang, J. R.

2008-01-01

In this study, we present an improved physical model to retrieve snowfall rate over land using brightness temperature observations from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Microwave Sounder Unit-B (AMSU-B) at 89 GHz, 150 GHz, 183.3 +/- 1 GHz, 183.3 +/- 3 GHz, and 183.3 +/- 7 GHz. The retrieval model is applied to the New England blizzard of March 5, 2001 which deposited about 75 cm of snow over much of Vermont, New Hampshire, and northern New York. In this improved physical model, prior retrieval assumptions about snowflake shape, particle size distributions, environmental conditions, and optimization methodology have been updated. Here, single scattering parameters for snow particles are calculated with the Discrete-Dipole Approximation (DDA) method instead of assuming spherical shapes. Five different snow particle models (hexagonal columns, hexagonal plates, and three different kinds of aggregates) are considered. Snow particle size distributions are assumed to vary with air temperature and to follow aircraft measurements described by previous studies. Brightness temperatures at AMSU-B frequencies for the New England blizzard are calculated using these DDA calculated single scattering parameters and particle size distributions. The vertical profiles of pressure, temperature, relative humidity and hydrometeors are provided by MM5 model simulations. These profiles are treated as the a priori data base in the Bayesian retrieval algorithm. In algorithm applications to the blizzard data, calculated brightness temperatures associated with selected database profiles agree with AMSU-B observations to within about +/- 5 K at all five frequencies. Retrieved snowfall rates compare favorably with the near-concurrent National Weather Service (NWS) radar reflectivity measurements. The relationships between the NWS radar measured reflectivities Z(sub e) and retrieved snowfall rate R for a given snow particle model are derived by a histogram matching technique. All of these Z(sub e)-R relationships fall in the range of previously established Z(sub e)-R relationships for snowfall. This suggests that the current physical model developed in this study can reliably estimate the snowfall rate over land using the AMSU-B measured brightness temperatures.

Projecting the long-term biogeochemical impacts of a diverse agroforestry system in the Midwest

NASA Astrophysics Data System (ADS)

Wolz, K. J.; DeLucia, E. H.; Paul, R. F.

2014-12-01

Annual, monoculture cropping systems have become the standard agricultural model in the Midwestern US. Unintended consequences of these systems include surface and groundwater pollution, greenhouse gas emissions, loss of biodiversity, and soil erosion. Diverse agroforestry (DA) systems dominated by fruit and nut trees/shrubs have been proposed as an agricultural model for the Midwestern US that can restore ecosystem services while simultaneously providing economically viable and industrially relevant staple food crops. A DA system including six species of fruit and nut crops was established on long-time conventional agricultural land at the University of Illinois at Urbana-Champaign in 2012, with the conventional corn-soybean rotation (CSR) as a control. Initial field measurements of the nitrogen and water cycles during the first two years of transition have indicated a significant decrease in N losses and modification of the seasonal evapotranspiration (ET) pattern. While these early results suggest that the land use transition from CSR to DA can have positive biogeochemical consequences, models must be utilized to make long-term biogeochemical projections in agroforestry systems. Initial field measurements of plant phenology, net N2O flux, nitrate leaching, soil respiration, and soil moisture were used to parameterize the DA system within the DayCENT biogeochemical model as the "savanna" ecosystem type. The model was validated with an independent subset of field measurements and then run to project biogeochemical cycling in the DA system for 25 years past establishment. Model results show that N losses via N2O emission or nitrate leaching reach a minimum within the first 5 years and then maintain this tight cycle into the future. While early ET field measurements revealed similar magnitudes between the DA and CSR systems, modeled ET continued to increase for the DA system throughout the projected time since the trees would continue to grow larger. These modeling results illustrate the potential long-term biogeochemical impacts that can be generated by a land-use transition to a diverse agroforestry system in the Midwest.

The Soil Moisture Active and Passive (SMAP) Mission

NASA Technical Reports Server (NTRS)

Entekhabi, Dara; Nijoku, Eni G.; ONeill, Peggy E.; Kellogg, Kent H.; Crow, Wade T.; Edelstein, Wendy N.; Entin, Jared K.; Goodman, Shawn D.; Jackson, Thomas J.; Johnson, Joel;

Two-dimensional simulation and modeling in scanning electron microscope imaging and metrology research.

PubMed

Postek, Michael T; Vladár, András E; Lowney, Jeremiah R; Keery, William J

2002-01-01

Traditional Monte Carlo modeling of the electron beam-specimen interactions in a scanning electron microscope (SEM) produces information about electron beam penetration and output signal generation at either a single beam-landing location, or multiple landing positions. If the multiple landings lie on a line, the results can be graphed in a line scan-like format. Monte Carlo results formatted as line scans have proven useful in providing one-dimensional information about the sample (e.g., linewidth). When used this way, this process is called forward line scan modeling. In the present work, the concept of image simulation (or the first step in the inverse modeling of images) is introduced where the forward-modeled line scan data are carried one step further to construct theoretical two-dimensional (2-D) micrographs (i.e., theoretical SEM images) for comparison with similar experimentally obtained micrographs. This provides an ability to mimic and closely match theory and experiment using SEM images. Calculated and/or measured libraries of simulated images can be developed with this technique. The library concept will prove to be very useful in the determination of dimensional and other properties of simple structures, such as integrated circuit parts, where the shape of the features is preferably measured from a single top-down image or a line scan. This paper presents one approach to the generation of 2-D simulated images and presents some suggestions as to their application to critical dimension metrology.

Models, Tools, and Databases for Land and Waste Management Research

EPA Pesticide Factsheets

These publicly available resources can be used for such tasks as simulating biodegradation or remediation of contaminants such as hydrocarbons, measuring sediment accumulation at superfund sites, or assessing toxicity and risk.

Understanding SMAP-L4 soil moisture estimation skill and their dependence with topography, precipitation and vegetation type using Mesonet and Micronet networks.

NASA Astrophysics Data System (ADS)

Moreno, H. A.; Basara, J. B.; Thompson, E.; Bertrand, D.; Johnston, C. S.

2017-12-01

Soil moisture measurements using satellite information can benefit from a land data assimilation model Goddard Earth Observing System (GEOS-5) and land data assimilation system (LDAS) to improve the representation of fine-scale dynamics and variability. This work presents some advances to understand the predictive skill of L4-SM product across different land-cover types, topography and precipitation totals, by using a dense network of multi-level soil moisture sensors (i.e. Mesonet and Micronet) in Oklahoma. 130 soil moisture stations are used across different precipitation gradients (i.e. arid vs wet), land cover (e.g. forest, shrubland, grasses, crops), elevation (low, mid and high) and slope to assess the improvements by the L4_SM product relative to the raw SMAP L-band brightness temperatures. The comparisons are conducted between July 2015 and July 2016 at the daily time scale. Results show the highest L4-SM overestimations occur in pastures and cultivated crops, during the rainy season and at higher elevation lands (over 800 meters asl). The smallest errors occur in low elevation lands, low rainfall and developed lands. Forested area's soil moisture biases lie in between pastures (max biases) and low intensity/developed lands (min biases). Fine scale assessment of L4-SM should help GEOS-5 and LDAS teams refine model parameters in light of observed differences and improve assimilation techniques in light of land-cover, topography and precipitation regime. Additionally, regional decision makers could have a framework to weight the utility of this product for water resources applications.

Cross-compartment evaluation of a fully-coupled hydrometeorological modeling system using comprehensive observation data

NASA Astrophysics Data System (ADS)

Fersch, Benjamin; Senatore, Alfonso; Kunstmann, Harald

2017-04-01

Fully-coupled hydrometeorological modeling enables investigations about the complex and often non-linear exchange mechanisms among subsurface, land, and atmosphere with respect to water and energy fluxes. The consideration of lateral redistribution of surface and subsurface water in such modeling systems is a crucial enhancement, allowing for a better representation of surface spatial patterns and providing also channel discharge predictions. However, the evaluation of fully-coupled simulations is difficult since the amount of physical detail along with feedback mechanisms leads to high degrees of freedom. Therefore, comprehensive observation data is required to obtain meaningful model configurations. We present a case study for a medium-sized river catchment in southern Germany that includes the calibration of the stand-alone and the evaluation of the fully-coupled WRF-Hydro modeling system with a horizontal resolution of 1 x 1 km2, for the period June to August 2015. ECMWF ERA-Interim reanalysis is used for model driving. Land-surface processes are represented by the Noah-MP land surface model. Land-cover is described by the EU CORINE data set. Observations for model evaluation are obtained from the TERENO Pre-Alpine observatory (http://www.imk-ifu.kit.edu/tereno.php) and are complemented by further measurements from the ScaleX campaign (http://scalex.imk-ifu.kit.edu) such as atmospheric profiles obtained from radiometer sounding and airborne systems as well as soil moisture and -temperature networks. We show how well water budgets and heat-fluxes are being reproduced by the stand-alone WRF, the stand-alone WRF-Hydro and the fully-coupled WRF-Hydro model.

Describing Ecosystem Complexity through Integrated Catchment Modeling

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J. D.; Peiffer, S.

2011-12-01

Land use and climate change have been implicated in reduced ecosystem services (ie: high quality water yield, biodiversity, and agricultural yield. The prediction of ecosystem services expected under future land use decisions and changing climate conditions has become increasingly important. Complex policy and management decisions require the integration of physical, economic, and social data over several scales to assess effects on water resources and ecology. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. A variety of models are being used to simulate plot and field scale experiments within the catchment. Results from each of the local-scale models provide identification of sensitive, local-scale parameters which are then used as inputs into a large-scale watershed model. We used the spatially distributed SWAT model to synthesize the experimental field data throughout the catchment. The approach of our study was that the range in local-scale model parameter results can be used to define the sensitivity and uncertainty in the large-scale watershed model. Further, this example shows how research can be structured for scientific results describing complex ecosystems and landscapes where cross-disciplinary linkages benefit the end result. The field-based and modeling framework described is being used to develop scenarios to examine spatial and temporal changes in land use practices and climatic effects on water quantity, water quality, and sediment transport. Development of accurate modeling scenarios requires understanding the social relationship between individual and policy driven land management practices and the value of sustainable resources to all shareholders.

Status of Air Quality in Central California and Needs for Further Study

NASA Astrophysics Data System (ADS)

Tanrikulu, S.; Beaver, S.; Soong, S.; Tran, C.; Jia, Y.; Matsuoka, J.; McNider, R. T.; Biazar, A. P.; Palazoglu, A.; Lee, P.; Wang, J.; Kang, D.; Aneja, V. P.

2012-12-01

Ozone and PM2.5 levels frequently exceed NAAQS in central California (CC). Additional emission reductions are needed to attain and maintain the standards there. Agencies are developing cost-effective emission control strategies along with complementary incentive programs to reduce emissions when exceedances are forecasted. These approaches require accurate modeling and forecasting capabilities. A variety of models have been rigorously applied (MM5, WRF, CMAQ, CAMx) over CC. Despite the vast amount of land-based measurements from special field programs and significant effort, models have historically exhibited marginal performance. Satellite data may improve model performance by: establishing IC/BC over outlying areas of the modeling domain having unknown conditions; enabling FDDA over the Pacific Ocean to characterize important marine inflows and pollutant outflows; and filling in the gaps of the land-based monitoring network. BAAQMD, in collaboration with the NASA AQAST, plans to conduct four studies that include satellite-based data in CC air quality analysis and modeling: The first project enhances and refines weather patterns, especially aloft, impacting summer ozone formation. Surface analyses were unable to characterize the strong attenuating effect of the complex terrain to steer marine winds impinging on the continent. The dense summer clouds and fog over the Pacific Ocean form spatial patterns that can be related to the downstream air flows through polluted areas. The goal of this project is to explore, characterize, and quantify these relationships using cloud cover data. Specifically, cloud agreement statistics will be developed using satellite data and model clouds. Model skin temperature predictions will be compared to both MODIS and GOES skin temperatures. The second project evaluates and improves the initial and simulated fields of meteorological models that provide inputs to air quality models. The study will attempt to determine whether a cloud dynamical adjustment developed by UAHuntsville can improve model performance for maritime stratus and whether a moisture adjustment scheme in the Pleim-Xiu boundary layer scheme can use satellite data in place of coarse surface air temperature measurements. The goal is to improve meteorological model performance that leads to improved air quality model performance. The third project evaluates and improves forecasting skills of the National Air Quality Forecasting Model in CC by using land-based routine measurements as well as satellite data. Local forecasts are mostly based on surface meteorological and air quality measurements and weather charts provided by NWS. The goal is to improve the average accuracy in forecasting exceedances, which is around 60%. The fourth project uses satellite data for monitoring trends in fine particulate matter (PM2.5) in the San Francisco Bay Area. It evaluates the effectiveness of a rule adopted in 2008 that restricts household wood burning on days forecasted to have high PM2.5 levels. The goal is to complement current analyses based on surface data covering the largest sub-regions and population centers. The overall goal is to use satellite data to overcome limitations of land-based measurements. The outcomes will be further conceptual understanding of pollutant formation, improved regulatory model performance, and better optimized forecasting programs.

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

USGS Publications Warehouse

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

2015-01-01

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

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

DOE PAGES

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

2015-07-28

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

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

Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.

Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate–carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimationmore » system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model–data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. Furthermore, the new improved parameters for JULES are presented along with the associated uncertainties for each parameter.« less

Improved daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed.

PubMed

Grimm, J W; Lynch, J A

2005-06-01

Daily precipitation nitrate and ammonium concentration models were developed for the Chesapeake Bay Watershed (USA) using a linear least-squares regression approach and precipitation chemistry data from 29 National Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites. Only weekly samples that comprised a single precipitation event were used in model development. The most significant variables in both ammonium and nitrate models included: precipitation volume, the number of days since the last event, a measure of seasonality, latitude, and the proportion of land within 8km covered by forest or devoted to industry and transportation. Additional variables included in the nitrate model were the proportion of land within 0.8km covered by water and/or forest. Local and regional ammonia and nitrogen oxide emissions were not as well correlated as land cover. Modeled concentrations compared very well with event chemistry data collected at six NADP/AirMoN sites within the Chesapeake Bay Watershed. Wet deposition estimates were also consistent with observed deposition at selected sites. Accurately describing the spatial distribution of precipitation volume throughout the watershed is important in providing critical estimates of wet-fall deposition of ammonium and nitrate.

Validating HYLARSMET: a Hydrologically Consistent Land Surface Model for Soil Moisture and Evapotranspiration Modelling over Southern Africa using Remote Sensing and Meteorological Data

NASA Astrophysics Data System (ADS)

Sinclair, Scott; Pegram, Geoff; Mengitsu, Michael; Everson, Colin

2015-04-01

Timeous knowledge of the spatial distribution of soil moisture and evapotranspiration over a large region in fine detail has great value for coping with two weather extremes: flash floods and droughts, since the state of the wetness of the land surface has a major impact on runoff response. Also, the ability to monitor the wetness of the soil and the actual evapotranspiration over large regions, without having to laboriously take expensive samples, is a bonus for agricultural managers who need to predict crop yields. We present samples of the daily national Soil Moisture and Evapotranspiration estimates on a grid of 7300 locations centred in 12 km squares, then move on to the results of a validation study for soil moisture and evapotranspiration estimated using the PyTOPKAPI hydrological model in Land Surface Modelling mode, a system called HYLARSMET. The HYLARSMET estimates are compared with detailed evapotranspiration and soil moisture measurements made at the Baynesfield experimental farm in the KwaZulu-Natal province of South Africa, run by the University of KZN. The HYLARSMET evapotranspiration estimates compared very well with the measured estimates for the two chosen crop types, in spite of the fact that the HYLARSMET estimates were not designed to explicitly account for the crop types at each site. The same seasonality effects were evident in all 3 estimates, and there was a stronger ET relationship between HYLARSMET and the Soybean site (Pearson r = 0.81) than for Maize, (r = 0.59). The soil moisture relationship was stronger between the two in situ measured estimates (r = 0.98 at 0.5 m depth) than it was between HYLARSMET and the field estimates (r about 0.52 in both cases). Overall there was a reasonably good relationship between HYLARSMET and the in situ measurements of ET and SM at each site, indicating the value of the modelling procedure.