Regional-scale integration of hydrological and geophysical data using Bayesian sequential simulation: application to field data

NASA Astrophysics Data System (ADS)

Ruggeri, Paolo; Irving, James; Gloaguen, Erwan; Holliger, Klaus

2013-04-01

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches to the regional scale still represents a major challenge, yet is critically important for the development of groundwater flow and contaminant transport models. To address this issue, we have developed a regional-scale hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure. The objective is to simulate the regional-scale distribution of a hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, our approach first involves linking the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. We present the application of this methodology to a pertinent field scenario, where we consider collocated high-resolution measurements of the electrical conductivity, measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, estimated from EM flowmeter and slug test measurements, in combination with low-resolution exhaustive electrical conductivity estimates obtained from dipole-dipole ERT meausurements.

Geochemical signature of land-based activities in Caribbean coral surface samples

USGS Publications Warehouse

Prouty, N.G.; Hughen, K.A.; Carilli, J.

2008-01-01

Anthropogenic threats, such as increased sedimentation, agrochemical run-off, coastal development, tourism, and overfishing, are of great concern to the Mesoamerican Caribbean Reef System (MACR). Trace metals in corals can be used to quantify and monitor the impact of these land-based activities. Surface coral samples from the MACR were investigated for trace metal signatures resulting from relative differences in water quality. Samples were analyzed at three spatial scales (colony, reef, and regional) as part of a hierarchical multi-scale survey. A primary goal of the paper is to elucidate the extrapolation of information between fine-scale variation at the colony or reef scale and broad-scale patterns at the regional scale. Of the 18 metals measured, five yielded statistical differences at the colony and/or reef scale, suggesting fine-scale spatial heterogeneity not conducive to regional interpretation. Five metals yielded a statistical difference at the regional scale with an absence of a statistical difference at either the colony or reef scale. These metals are barium (Ba), manganese (Mn), chromium (Cr), copper (Cu), and antimony (Sb). The most robust geochemical indicators of land-based activities are coral Ba and Mn concentrations, which are elevated in samples from the southern region of the Gulf of Honduras relative to those from the Turneffe Islands. These findings are consistent with the occurrence of the most significant watersheds in the MACR from southern Belize to Honduras, which contribute sediment-laden freshwater to the coastal zone primarily as a result of human alteration to the landscape (e.g., deforestation and agricultural practices). Elevated levels of Cu and Sb were found in samples from Honduras and may be linked to industrial shipping activities where copper-antimony additives are commonly used in antifouling paints. Results from this study strongly demonstrate the impact of terrestrial runoff and anthropogenic activities on coastal water quality in the MACR. ?? 2008 Springer-Verlag.

Flash-Flood hydrological simulations at regional scale. Scale signature on road flooding vulnerability

NASA Astrophysics Data System (ADS)

Anquetin, Sandrine; Vannier, Olivier; Ollagnier, Mélody; Braud, Isabelle

2015-04-01

This work contributes to the evaluation of the dynamics of the human exposure during flash-flood events in the Mediterranean region. Understanding why and how the commuters modify their daily mobility in the Cévennes - Vivarais area (France) is the long-term objective of the study. To reach this objective, the methodology relies on three steps: i) evaluation of daily travel patterns, ii) reconstitution of road flooding events in the region based on hydrological simulation at regional scale in order to capture the time evolution and the intensity of flood and iii) identification of the daily fluctuation of the exposition according to road flooding scenarios and the time evolution of mobility patterns. This work deals with the second step. To do that, the physically based and non-calibrated hydrological model CVN (Vannier, 2013) is implemented to retrieve the hydrological signature of past flash-flood events in Southern France. Four past events are analyzed (September 2002; September 2005 (split in 2 different events); October 2008). Since the regional scale is investigated, the scales of the studied catchments range from few km2 to few hundreds of km2 where many catchments are ungauged. The evaluation is based on a multi-scale approach using complementary observations coming from post-flood experiments (for small and/or ungaugged catchments) and operational hydrological network (for larger catchments). The scales of risk (time and location of the road flooding) are also compared to observed data of road cuts. The discussion aims at improving our understanding on the hydrological processes associated with road flooding vulnerability. We specifically analyze runoff coefficient and the ratio between surface and groundwater flows at regional scale. The results show that on the overall, the three regional simulations provide good scores for the probability of detection and false alarms concerning road flooding (1600 points are analyzed for the whole region). Our evaluation procedure provides new insights on the active hydrological processes at small scales (catchments area < 10 km²) since these small scales, distributed over the whole region, are analyzed through road cuts data and post-flood field investigations. As shown in Vannier (2013), the signature of the altered geological layer is significant on the simulated discharges. For catchments under schisty geology, the simulated discharge, whatever the catchment size, is usually overestimated. Vannier, O, 2013, Apport de la modélisation hydrologique régionale à la compréhension des processus de crue en zone méditerranéenne, PhD-Thesis (in French), Grenoble University.

Nonlinear effects of locally heterogeneous hydraulic conductivity fields on regional stream-aquifer exchanges

NASA Astrophysics Data System (ADS)

Zhu, J.; Winter, C. L.; Wang, Z.

2015-08-01

Computational experiments are performed to evaluate the effects of locally heterogeneous conductivity fields on regional exchanges of water between stream and aquifer systems in the Middle Heihe River Basin (MHRB) of northwestern China. The effects are found to be nonlinear in the sense that simulated discharges from aquifers to streams are systematically lower than discharges produced by a base model parameterized with relatively coarse effective conductivity. A similar, but weaker, effect is observed for stream leakage. The study is organized around three hypotheses: (H1) small-scale spatial variations of conductivity significantly affect regional exchanges of water between streams and aquifers in river basins, (H2) aggregating small-scale heterogeneities into regional effective parameters systematically biases estimates of stream-aquifer exchanges, and (H3) the biases result from slow-paths in groundwater flow that emerge due to small-scale heterogeneities. The hypotheses are evaluated by comparing stream-aquifer fluxes produced by the base model to fluxes simulated using realizations of the MHRB characterized by local (grid-scale) heterogeneity. Levels of local heterogeneity are manipulated as control variables by adjusting coefficients of variation. All models are implemented using the MODFLOW simulation environment, and the PEST tool is used to calibrate effective conductivities defined over 16 zones within the MHRB. The effective parameters are also used as expected values to develop log-normally distributed conductivity (K) fields on local grid scales. Stream-aquifer exchanges are simulated with K fields at both scales and then compared. Results show that the effects of small-scale heterogeneities significantly influence exchanges with simulations based on local-scale heterogeneities always producing discharges that are less than those produced by the base model. Although aquifer heterogeneities are uncorrelated at local scales, they appear to induce coherent slow-paths in groundwater fluxes that in turn reduce aquifer-stream exchanges. Since surface water-groundwater exchanges are critical hydrologic processes in basin-scale water budgets, these results also have implications for water resources management.

A Limited-Memory BFGS Algorithm Based on a Trust-Region Quadratic Model for Large-Scale Nonlinear Equations.

PubMed

Li, Yong; Yuan, Gonglin; Wei, Zengxin

2015-01-01

In this paper, a trust-region algorithm is proposed for large-scale nonlinear equations, where the limited-memory BFGS (L-M-BFGS) update matrix is used in the trust-region subproblem to improve the effectiveness of the algorithm for large-scale problems. The global convergence of the presented method is established under suitable conditions. The numerical results of the test problems show that the method is competitive with the norm method.

Inverse Modeling of Texas NOx Emissions Using Space-Based and Ground-Based NO2 Observations

NASA Technical Reports Server (NTRS)

Tang, Wei; Cohan, D.; Lamsal, L. N.; Xiao, X.; Zhou, W.

2013-01-01

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellitebased top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Regional climates in the GISS general circulation model: Surface air temperature

NASA Technical Reports Server (NTRS)

Hewitson, Bruce

1994-01-01

One of the more viable research techniques into global climate change for the purpose of understanding the consequent environmental impacts is based on the use of general circulation models (GCMs). However, GCMs are currently unable to reliably predict the regional climate change resulting from global warming, and it is at the regional scale that predictions are required for understanding human and environmental responses. Regional climates in the extratropics are in large part governed by the synoptic-scale circulation and the feasibility of using this interscale relationship is explored to provide a way of moving to grid cell and sub-grid cell scales in the model. The relationships between the daily circulation systems and surface air temperature for points across the continental United States are first developed in a quantitative form using a multivariate index based on principal components analysis (PCA) of the surface circulation. These relationships are then validated by predicting daily temperature using observed circulation and comparing the predicted values with the observed temperatures. The relationships predict surface temperature accurately over the major portion of the country in winter, and for half the country in summer. These relationships are then applied to the surface synoptic circulation of the Goddard Institute for Space Studies (GISS) GCM control run, and a set of surface grid cell temperatures are generated. These temperatures, based on the larger-scale validated circulation, may now be used with greater confidence at the regional scale. The generated temperatures are compared to those of the model and show that the model has regional errors of up to 10 C in individual grid cells.

On identifying relationships between the flood scaling exponent and basin attributes.

PubMed

Medhi, Hemanta; Tripathi, Shivam

2015-07-01

Floods are known to exhibit self-similarity and follow scaling laws that form the basis of regional flood frequency analysis. However, the relationship between basin attributes and the scaling behavior of floods is still not fully understood. Identifying these relationships is essential for drawing connections between hydrological processes in a basin and the flood response of the basin. The existing studies mostly rely on simulation models to draw these connections. This paper proposes a new methodology that draws connections between basin attributes and the flood scaling exponents by using observed data. In the proposed methodology, region-of-influence approach is used to delineate homogeneous regions for each gaging station. Ordinary least squares regression is then applied to estimate flood scaling exponents for each homogeneous region, and finally stepwise regression is used to identify basin attributes that affect flood scaling exponents. The effectiveness of the proposed methodology is tested by applying it to data from river basins in the United States. The results suggest that flood scaling exponent is small for regions having (i) large abstractions from precipitation in the form of large soil moisture storages and high evapotranspiration losses, and (ii) large fractions of overland flow compared to base flow, i.e., regions having fast-responding basins. Analysis of simple scaling and multiscaling of floods showed evidence of simple scaling for regions in which the snowfall dominates the total precipitation.

[Object-oriented segmentation and classification of forest gap based on QuickBird remote sensing image.

PubMed

Mao, Xue Gang; Du, Zi Han; Liu, Jia Qian; Chen, Shu Xin; Hou, Ji Yu

2018-01-01

Traditional field investigation and artificial interpretation could not satisfy the need of forest gaps extraction at regional scale. High spatial resolution remote sensing image provides the possibility for regional forest gaps extraction. In this study, we used object-oriented classification method to segment and classify forest gaps based on QuickBird high resolution optical remote sensing image in Jiangle National Forestry Farm of Fujian Province. In the process of object-oriented classification, 10 scales (10-100, with a step length of 10) were adopted to segment QuickBird remote sensing image; and the intersection area of reference object (RA or ) and intersection area of segmented object (RA os ) were adopted to evaluate the segmentation result at each scale. For segmentation result at each scale, 16 spectral characteristics and support vector machine classifier (SVM) were further used to classify forest gaps, non-forest gaps and others. The results showed that the optimal segmentation scale was 40 when RA or was equal to RA os . The accuracy difference between the maximum and minimum at different segmentation scales was 22%. At optimal scale, the overall classification accuracy was 88% (Kappa=0.82) based on SVM classifier. Combining high resolution remote sensing image data with object-oriented classification method could replace the traditional field investigation and artificial interpretation method to identify and classify forest gaps at regional scale.

Costs of delivering human papillomavirus vaccination to schoolgirls in Mwanza Region, Tanzania

PubMed Central

2012-01-01

Background Cervical cancer is the leading cause of female cancer-related deaths in Tanzania. Vaccination against human papillomavirus (HPV) offers a new opportunity to control this disease. This study aimed to estimate the costs of a school-based HPV vaccination project in three districts in Mwanza Region (NCT ID: NCT01173900), Tanzania and to model incremental scaled-up costs of a regional vaccination program. Methods We first conducted a top-down cost analysis of the vaccination project, comparing observed costs of age-based (girls born in 1998) and class-based (class 6) vaccine delivery in a total of 134 primary schools. Based on the observed project costs, we then modeled incremental costs of a scaled-up vaccination program for Mwanza Region from the perspective of the Tanzanian government, assuming that HPV vaccines would be delivered through the Expanded Programme on Immunization (EPI). Results Total economic project costs for delivering 3 doses of HPV vaccine to 4,211 girls were estimated at about US$349,400 (including a vaccine price of US$5 per dose). Costs per fully-immunized girl were lower for class-based delivery than for age-based delivery. Incremental economic scaled-up costs for class-based vaccination of 50,290 girls in Mwanza Region were estimated at US$1.3 million. Economic scaled-up costs per fully-immunized girl were US$26.41, including HPV vaccine at US$5 per dose. Excluding vaccine costs, vaccine could be delivered at an incremental economic cost of US$3.09 per dose and US$9.76 per fully-immunized girl. Financial scaled-up costs, excluding costs of the vaccine and salaries of existing staff were estimated at US$1.73 per dose. Conclusions Project costs of class-based vaccination were found to be below those of age-based vaccination because of more eligible girls being identified and higher vaccine uptake. We estimate that vaccine can be delivered at costs that would make HPV vaccination a very cost-effective intervention. Potentially, integrating HPV vaccine delivery with cost-effective school-based health interventions and a reduction of vaccine price below US$5 per dose would further reduce the costs per fully HPV-immunized girl. PMID:23148516

Costs of delivering human papillomavirus vaccination to schoolgirls in Mwanza Region, Tanzania.

PubMed

Quentin, Wilm; Terris-Prestholt, Fern; Changalucha, John; Soteli, Selephina; Edmunds, W John; Hutubessy, Raymond; Ross, David A; Kapiga, Saidi; Hayes, Richard; Watson-Jones, Deborah

2012-11-13

Cervical cancer is the leading cause of female cancer-related deaths in Tanzania. Vaccination against human papillomavirus (HPV) offers a new opportunity to control this disease. This study aimed to estimate the costs of a school-based HPV vaccination project in three districts in Mwanza Region (NCT ID: NCT01173900), Tanzania and to model incremental scaled-up costs of a regional vaccination program. We first conducted a top-down cost analysis of the vaccination project, comparing observed costs of age-based (girls born in 1998) and class-based (class 6) vaccine delivery in a total of 134 primary schools. Based on the observed project costs, we then modeled incremental costs of a scaled-up vaccination program for Mwanza Region from the perspective of the Tanzanian government, assuming that HPV vaccines would be delivered through the Expanded Programme on Immunization (EPI). Total economic project costs for delivering 3 doses of HPV vaccine to 4,211 girls were estimated at about US$349,400 (including a vaccine price of US$5 per dose). Costs per fully-immunized girl were lower for class-based delivery than for age-based delivery. Incremental economic scaled-up costs for class-based vaccination of 50,290 girls in Mwanza Region were estimated at US$1.3 million. Economic scaled-up costs per fully-immunized girl were US$26.41, including HPV vaccine at US$5 per dose. Excluding vaccine costs, vaccine could be delivered at an incremental economic cost of US$3.09 per dose and US$9.76 per fully-immunized girl. Financial scaled-up costs, excluding costs of the vaccine and salaries of existing staff were estimated at US$1.73 per dose. Project costs of class-based vaccination were found to be below those of age-based vaccination because of more eligible girls being identified and higher vaccine uptake. We estimate that vaccine can be delivered at costs that would make HPV vaccination a very cost-effective intervention. Potentially, integrating HPV vaccine delivery with cost-effective school-based health interventions and a reduction of vaccine price below US$5 per dose would further reduce the costs per fully HPV-immunized girl.

Spatial feature analysis of a cosmic-ray sensor for measuring the soil water content: Comparison of four weighting methods

NASA Astrophysics Data System (ADS)

Cai, Jingya; Pang, Zhiguo; Fu, Jun'e.

2018-04-01

To quantitatively analyze the spatial features of a cosmic-ray sensor (CRS) (i.e., the measurement support volume of the CRS and the weight of the in situ point-scale soil water content (SWC) in terms of the regionally averaged SWC derived from the CRS) in measuring the SWC, cooperative observations based on CRS, oven drying and frequency domain reflectometry (FDR) methods are performed at the point and regional scales in a desert steppe area of the Inner Mongolia Autonomous Region. This region is flat with sparse vegetation cover consisting of only grass, thereby minimizing the effects of terrain and vegetation. Considering the two possibilities of the measurement support volume of the CRS, the results of four weighting methods are compared with the SWC monitored by FDR within an appropriate measurement support volume. The weighted average calculated using the neutron intensity-based weighting method (Ni weighting method) best fits the regionally averaged SWC measured by the CRS. Therefore, we conclude that the gyroscopic support volume and the weights determined by the Ni weighting method are the closest to the actual spatial features of the CRS when measuring the SWC. Based on these findings, a scale transformation model of the SWC from the point scale to the scale of the CRS measurement support volume is established. In addition, the spatial features simulated using the Ni weighting method are visualized by developing a software system.

High-resolution, regional-scale crop yield simulations for the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D. H.; Kafatos, M.; Medvigy, D.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Prasad, A. K.; Tremback, C.; Walko, R. L.; Asrar, G. R.

2012-12-01

Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and maximum temperature), beyond which the yields were negatively affected. These results are now being used for further regional-scale yield analysis as the aforementioned framework is adaptable to multiple geographic regions and crop types.

Target matching based on multi-view tracking

NASA Astrophysics Data System (ADS)

Liu, Yahui; Zhou, Changsheng

2011-01-01

A feature matching method is proposed based on Maximally Stable Extremal Regions (MSER) and Scale Invariant Feature Transform (SIFT) to solve the problem of the same target matching in multiple cameras. Target foreground is extracted by using frame difference twice and bounding box which is regarded as target regions is calculated. Extremal regions are got by MSER. After fitted into elliptical regions, those regions will be normalized into unity circles and represented with SIFT descriptors. Initial matching is obtained from the ratio of the closest distance to second distance less than some threshold and outlier points are eliminated in terms of RANSAC. Experimental results indicate the method can reduce computational complexity effectively and is also adapt to affine transformation, rotation, scale and illumination.

Multi-scale statistical analysis of coronal solar activity

DOE PAGES

Gamborino, Diana; del-Castillo-Negrete, Diego; Martinell, Julio J.

2016-07-08

Multi-filter images from the solar corona are used to obtain temperature maps that are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions, we show that the multi-scale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also to be extracted from the analysis.

Causal inference between bioavailability of heavy metals and environmental factors in a large-scale region.

PubMed

Liu, Yuqiong; Du, Qingyun; Wang, Qi; Yu, Huanyun; Liu, Jianfeng; Tian, Yu; Chang, Chunying; Lei, Jing

2017-07-01

The causation between bioavailability of heavy metals and environmental factors are generally obtained from field experiments at local scales at present, and lack sufficient evidence from large scales. However, inferring causation between bioavailability of heavy metals and environmental factors across large-scale regions is challenging. Because the conventional correlation-based approaches used for causation assessments across large-scale regions, at the expense of actual causation, can result in spurious insights. In this study, a general approach framework, Intervention calculus when the directed acyclic graph (DAG) is absent (IDA) combined with the backdoor criterion (BC), was introduced to identify causation between the bioavailability of heavy metals and the potential environmental factors across large-scale regions. We take the Pearl River Delta (PRD) in China as a case study. The causal structures and effects were identified based on the concentrations of heavy metals (Zn, As, Cu, Hg, Pb, Cr, Ni and Cd) in soil (0-20 cm depth) and vegetable (lettuce) and 40 environmental factors (soil properties, extractable heavy metals and weathering indices) in 94 samples across the PRD. Results show that the bioavailability of heavy metals (Cd, Zn, Cr, Ni and As) was causally influenced by soil properties and soil weathering factors, whereas no causal factor impacted the bioavailability of Cu, Hg and Pb. No latent factor was found between the bioavailability of heavy metals and environmental factors. The causation between the bioavailability of heavy metals and environmental factors at field experiments is consistent with that on a large scale. The IDA combined with the BC provides a powerful tool to identify causation between the bioavailability of heavy metals and environmental factors across large-scale regions. Causal inference in a large system with the dynamic changes has great implications for system-based risk management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting Future-Year Ozone Concentrations: Integrated Observational-Modeling Approach for Probabilistic Evaluation of the Efficacy of Emission Control strategies

EPA Science Inventory

Regional-scale air quality models are being used to demonstrate attainment of the ozone air quality standard. In current regulatory applications, a regional-scale air quality model is applied for a base year and a future year with reduced emissions using the same meteorological ...

INDICATORS OF ECOLOGICAL STRESS AND THEIR EXTENT IN THE POPULATION OF NORTHEASTERN LAKES: A REGIONAL-SCALE ASSESSMENT

EPA Science Inventory

One of the Environmental Monitoring and Assessment Program's first projects was a survey of 345 lakes in the eight states of the Northeast, during summers of 1991-1996. This survey was the first regional-scale attempt to use a probability-based sampling design to collect biolog...

Taking the pulse of a continent: Expanding site-based research infrastructure for regional- to continental-scale ecology

USDA-ARS?s Scientific Manuscript database

Many of the most dramatic and surprising effects of global change on ecological systems will occur across large spatial extents, from regions to continents. Multiple ecosystem types will be impacted across a range of interacting spatial and temporal scales. The ability of ecologists to understand an...

Indicators of climate change in Idaho: An assessment framework for coupling biophysical change and social perception

USDA-ARS?s Scientific Manuscript database

Climate change is well documented at the global scale, but local and regional changes are not as well understood. Finer, local-to-regional scale information is needed for creating specific, place-based planning and adaption efforts. Here we detail the development of an indicator-focused climate chan...

Global maps of the magnetic thickness and magnetization of the Earth's lithosphere

NASA Astrophysics Data System (ADS)

Vervelidou, Foteini; Thébault, Erwan

2015-10-01

We have constructed global maps of the large-scale magnetic thickness and magnetization of Earth's lithosphere. Deriving such large-scale maps based on lithospheric magnetic field measurements faces the challenge of the masking effect of the core field. In this study, the maps were obtained through analyses in the spectral domain by means of a new regional spatial power spectrum based on the Revised Spherical Cap Harmonic Analysis (R-SCHA) formalism. A series of regional spectral analyses were conducted covering the entire Earth. The R-SCHA surface power spectrum for each region was estimated using the NGDC-720 spherical harmonic (SH) model of the lithospheric magnetic field, which is based on satellite, aeromagnetic, and marine measurements. These observational regional spectra were fitted to a recently proposed statistical expression of the power spectrum of Earth's lithospheric magnetic field, whose free parameters include the thickness and magnetization of the magnetic sources. The resulting global magnetic thickness map is compared to other crustal and magnetic thickness maps based upon different geophysical data. We conclude that the large-scale magnetic thickness of the lithosphere is on average confined to a layer that does not exceed the Moho.

Nonlinear effects of locally heterogeneous hydraulic conductivity fields on regional stream-aquifer exchanges

NASA Astrophysics Data System (ADS)

Zhu, J.; Winter, C. L.; Wang, Z.

2015-11-01

Computational experiments are performed to evaluate the effects of locally heterogeneous conductivity fields on regional exchanges of water between stream and aquifer systems in the Middle Heihe River basin (MHRB) of northwestern China. The effects are found to be nonlinear in the sense that simulated discharges from aquifers to streams are systematically lower than discharges produced by a base model parameterized with relatively coarse effective conductivity. A similar, but weaker, effect is observed for stream leakage. The study is organized around three hypotheses: (H1) small-scale spatial variations of conductivity significantly affect regional exchanges of water between streams and aquifers in river basins, (H2) aggregating small-scale heterogeneities into regional effective parameters systematically biases estimates of stream-aquifer exchanges, and (H3) the biases result from slow paths in groundwater flow that emerge due to small-scale heterogeneities. The hypotheses are evaluated by comparing stream-aquifer fluxes produced by the base model to fluxes simulated using realizations of the MHRB characterized by local (grid-scale) heterogeneity. Levels of local heterogeneity are manipulated as control variables by adjusting coefficients of variation. All models are implemented using the MODFLOW (Modular Three-dimensional Finite-difference Groundwater Flow Model) simulation environment, and the PEST (parameter estimation) tool is used to calibrate effective conductivities defined over 16 zones within the MHRB. The effective parameters are also used as expected values to develop lognormally distributed conductivity (K) fields on local grid scales. Stream-aquifer exchanges are simulated with K fields at both scales and then compared. Results show that the effects of small-scale heterogeneities significantly influence exchanges with simulations based on local-scale heterogeneities always producing discharges that are less than those produced by the base model. Although aquifer heterogeneities are uncorrelated at local scales, they appear to induce coherent slow paths in groundwater fluxes that in turn reduce aquifer-stream exchanges. Since surface water-groundwater exchanges are critical hydrologic processes in basin-scale water budgets, these results also have implications for water resources management.

Inflated Uncertainty in Multimodel-Based Regional Climate Projections.

PubMed

Madsen, Marianne Sloth; Langen, Peter L; Boberg, Fredrik; Christensen, Jens Hesselbjerg

2017-11-28

Multimodel ensembles are widely analyzed to estimate the range of future regional climate change projections. For an ensemble of climate models, the result is often portrayed by showing maps of the geographical distribution of the multimodel mean results and associated uncertainties represented by model spread at the grid point scale. Here we use a set of CMIP5 models to show that presenting statistics this way results in an overestimation of the projected range leading to physically implausible patterns of change on global but also on regional scales. We point out that similar inconsistencies occur in impact analyses relying on multimodel information extracted using statistics at the regional scale, for example, when a subset of CMIP models is selected to represent regional model spread. Consequently, the risk of unwanted impacts may be overestimated at larger scales as climate change impacts will never be realized as the worst (or best) case everywhere.

Assessment of the spatial scaling behaviour of floods in the United Kingdom

NASA Astrophysics Data System (ADS)

Formetta, Giuseppe; Stewart, Elizabeth; Bell, Victoria

2017-04-01

Floods are among the most dangerous natural hazards, causing loss of life and significant damage to private and public property. Regional flood-frequency analysis (FFA) methods are essential tools to assess the flood hazard and plan interventions for its mitigation. FFA methods are often based on the well-known index flood method that assumes the invariance of the coefficient of variation of floods with drainage area. This assumption is equivalent to the simple scaling or self-similarity assumption for peak floods, i.e. their spatial structure remains similar in a particular, relatively simple, way to itself over a range of scales. Spatial scaling of floods has been evaluated at national scale for different countries such as Canada, USA, and Australia. According our knowledge. Such a study has not been conducted for the United Kingdom even though the standard FFA method there is based on the index flood assumption. In this work we present an integrated approach to assess of the spatial scaling behaviour of floods in the United Kingdom using three different methods: product moments (PM), probability weighted moments (PWM), and quantile analysis (QA). We analyse both instantaneous and daily annual observed maximum floods and performed our analysis both across the entire country and in its sub-climatic regions as defined in the Flood Studies Report (NERC, 1975). To evaluate the relationship between the k-th moments or quantiles and the drainage area we used both regression with area alone and multiple regression considering other explanatory variables to account for the geomorphology, amount of rainfall, and soil type of the catchments. The latter multiple regression approach was only recently demonstrated being more robust than the traditional regression with area alone that can lead to biased estimates of scaling exponents and misinterpretation of spatial scaling behaviour. We tested our framework on almost 600 rural catchments in UK considered as entire region and split in 11 sub-regions with 50 catchments per region on average. Preliminary results from the three different spatial scaling methods are generally in agreement and indicate that: i) only some of the peak flow variability is explained by area alone (approximately 50% for the entire country and ranging between the 40% and 70% for the sub-regions); ii) this percentage increases to 90% for the entire country and ranges between 80% and 95% for the sub-regions when the multiple regression is used; iii) the simple scaling hypothesis holds in all sub-regions with the exception of weak multi-scaling found in the regions 2 (North), and 5 and 6 (South East). We hypothesize that these deviations can be explained by heterogeneity in large scale precipitation and by the influence of the soil type (predominantly chalk) on the flood formation process in regions 5 and 6.

An interdisciplinary assessment of regional-scale nonpoint source ground-water vulnerability; theory and application

USGS Publications Warehouse

Bernknopf, Richard L.; Dinitz, Laura B.; Loague, Keith

2001-01-01

An integrated earth science-economics model, developed within a geographic information system (GIS), combines a regional-scale nonpoint source vulnerability assessment with a specific remediation measure to avoid unnecessary agricultural production costs associated with the use of agrochemicals in the Pearl Harbor basin on the island of Oahu, Hawaii. This approach forms the core of a risk-based regulation for the application of agrochemicals and estimates the benefits of an information-based approach to decisionmaking.

Using satellite-based measurements to explore spatiotemporal scales and variability of drivers of new particle formation

EPA Science Inventory

New particle formation (NPF) can potentially alter regional climate by increasing aerosol particle (hereafter particle) number concentrations and ultimately cloud condensation nuclei. The large scales on which NPF is manifest indicate potential to use satellite-based (inherently ...

Scaling violation in fragmentation region at energies above 10-15 eV based on the data on cosmic ray hadron component

NASA Technical Reports Server (NTRS)

1985-01-01

The ratio of intensity of energetic hadrons, having no visible accompaniment, to the total flux of hadrons of the same energy at 4380m above sea level is given. The ratio is much more than expected for scaling model with proton primaries. This result could not be explained by complex chemical composition of primary cosmic ray and indicates the scaling violation in fragmentation region.

Multi-temporal monitoring of a regional riparian buffer network (>12,000 km) with LiDAR and photogrammetric point clouds.

PubMed

Michez, Adrien; Piégay, Hervé; Lejeune, Philippe; Claessens, Hugues

2017-11-01

Riparian buffers are of major concern for land and water resource managers despite their relatively low spatial coverage. In Europe, this concern has been acknowledged by different environmental directives which recommend multi-scale monitoring (from local to regional scales). Remote sensing methods could be a cost-effective alternative to field-based monitoring, to build replicable "wall-to-wall" monitoring strategies of large river networks and associated riparian buffers. The main goal of our study is to extract and analyze various parameters of the riparian buffers of up to 12,000 km of river in southern Belgium (Wallonia) from three-dimensional (3D) point clouds based on LiDAR and photogrammetric surveys to i) map riparian buffers parameters on different scales, ii) interpret the regional patterns of the riparian buffers and iii) propose new riparian buffer management indicators. We propose different strategies to synthesize and visualize relevant information at different spatial scales ranging from local (<10 km) to regional scale (>12,000 km). Our results showed that the selected parameters had a clear regional pattern. The reaches of Ardenne ecoregion have channels with the highest flow widths and shallowest depths. In contrast, the reaches of the Loam ecoregion have the narrowest and deepest flow channels. Regional variability in channel width and depth is used to locate management units potentially affected by human impact. Riparian forest of the Loam ecoregion is characterized by the lowest longitudinal continuity and mean tree height, underlining significant human disturbance. As the availability of 3D point clouds at the regional scale is constantly growing, our study proposes reproducible methods which can be integrated into regional monitoring by land managers. With LiDAR still being relatively expensive to acquire, the use of photogrammetric point clouds combined with LiDAR data is a cost-effective means to update the characterization of the riparian forest conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Atmosphere

NASA Astrophysics Data System (ADS)

Ghosh, D.; Mitra, S. K.

2014-05-01

This paper investigates the high-temperature corrosion behavior of microstructurally different regions of the weldment of 9 Cr-1 Mo steel used in thermal power plant boiler in SO2 + O2 environment. The weldment is produced by tungsten inert gas welding method, and the different regions of the weldment (weld metal, heat-affected zone, and base metal) are exposed in SO2 + O2 (ratio 2:1) environment at 973 K for 120 h. The reaction kinetics and corrosion growth rate of different regions of weldment in isothermal condition are evaluated. The post corroded scales of the different specimens are studied in SEM, EDS, and XRD. The results indicate that the weld metal shows higher corrosion rate followed by HAZ and base metal. The higher rate of corrosion of weldmetal is mainly attributed to the least protective inner scale of Cr2O3 with minimum Cr Content. This is due to the formation of delta ferrite, which leads to the precipitation of the Cr-based secondary phases and depletes the free Cr from the matrix. The thermal cycles during welding at high temperature are favorable for the formation of delta ferrite. On the other hand, in absence of delta ferrite, the base metal and HAZ regions of the weldment show lower corrosion rate than weld metal. The difference in corrosion rate in the three regions of the weldment is supplemented by post-corroded scale characterizations.

Quantifying oceanic moisture exports to mainland China in association with summer precipitation

NASA Astrophysics Data System (ADS)

Chen, Bin; Xu, Xiang-De; Zhao, TianLiang

2017-10-01

Oceanic moisture exports (OMEs) are considered the major moisture sources for precipitation over Mainland China during the boreal summer season. In this study, a Lagrangian particle dispersion and transport model [FLEXible PARTicle dispersion model (FLEXPART)] driven with European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA)-Interim data was used to conduct 35-year modeling of the summer season (May-August) for 1980-2014. Based on the 6-h output over 35 years, a relatively sophisticated approach was adopted that considers the change in specific humidity with trajectory tracking to diagnose OME-based precipitation during the summer season in China. We specifically explored the spatiotemporal structure of OME-based precipitation over Mainland China with a focus on quantifying the relative contributions of three specific oceanic sub-regions: the Arabian Sea (AS), the Bay of Bengal (BOB), and the South China Sea (SCS). The relevance of the OME anomalies from the three sub-regions and the observed precipitation changes on an interannual scale were also explored. The main research conclusions are summarized as follows: (1) The diagnosed OME-based precipitation and gauge observations exhibit similar spatial patterns in both seasonal and sub-seasonal scales, further evidencing the robustness of the approach used in this study. (2) Climatologically, the OMEs originating from the AS, the BOB, and the SCS made roughly equivalent contributions to the entire areal-averaged precipitation over Mainland China on a seasonal scale, but the preferred regions influenced by the three oceanic sources differ strongly from each other. (3) The relative contributions of OME from three specific subsections to precipitation varied significantly on the sub-seasonal scale. During the onset of summer monsoons, the AS region ranked first as an important oceanic source, followed by the BOB and the SCS, whereas during the withdrawal of summer monsoons, this order was reversed. (4) The interannual anomalies of OME-based precipitation from the SCS and the BOB regions are negatively correlated with those outside the AS region.

GIS-based regionalized life cycle assessment: how big is small enough? Methodology and case study of electricity generation.

PubMed

Mutel, Christopher L; Pfister, Stephan; Hellweg, Stefanie

2012-01-17

We describe a new methodology for performing regionalized life cycle assessment and systematically choosing the spatial scale of regionalized impact assessment methods. We extend standard matrix-based calculations to include matrices that describe the mapping from inventory to impact assessment spatial supports. Uncertainty in inventory spatial data is modeled using a discrete spatial distribution function, which in a case study is derived from empirical data. The minimization of global spatial autocorrelation is used to choose the optimal spatial scale of impact assessment methods. We demonstrate these techniques on electricity production in the United States, using regionalized impact assessment methods for air emissions and freshwater consumption. Case study results show important differences between site-generic and regionalized calculations, and provide specific guidance for future improvements of inventory data sets and impact assessment methods.

Comparing different methods for determining forest evapotranspiration and its components at multiple temporal scales.

PubMed

Tie, Qiang; Hu, Hongchang; Tian, Fuqiang; Holbrook, N Michele

2018-08-15

Accurately estimating forest evapotranspiration and its components is of great importance for hydrology, ecology, and meteorology. In this study, a comparison of methods for determining forest evapotranspiration and its components at annual, monthly, daily, and diurnal scales was conducted based on in situ measurements in the subhumid mountainous forest of North China. The goal of the study was to evaluate the accuracies and reliabilities of the different methods. The results indicate the following: (1) The sap flow upscaling procedure, taking into account diversities in forest types and tree species, produced component-based forest evapotranspiration estimate that agreed with eddy covariance-based estimate at the temporal scales of year, month, and day, while soil water budget-based forest evapotranspiration estimate was also qualitatively consistent with eddy covariance-based estimate at the daily scale; (2) At the annual scale, catchment water balance-based forest evapotranspiration estimate was significantly higher than eddy covariance-based estimate, which might probably result from non-negligible subsurface runoff caused by the widely distributed regolith and fractured bedrock under the ground; (3) At the sub-daily scale, the diurnal course of sap flow based-canopy transpiration estimate lagged significantly behind eddy covariance-based forest evapotranspiration estimate, which might physiologically be due to stem water storage and stem hydraulic conductivity. The results in this region may have much referential significance for forest evapotranspiration estimation and method evaluation in regions with similar environmental conditions. Copyright © 2018 Elsevier B.V. All rights reserved.

Moon-based visibility analysis for the observation of “The Belt and Road”

NASA Astrophysics Data System (ADS)

REN, Yuanzhen; GUO, Huadong; LIU, Guang; YE, Hanlin; DING, Yixing; RUAN, Zhixing; LV, Mingyang

2016-11-01

Aiming at promoting the economic prosperity and regional economic cooperation, the “Silk Road Economic Belt” and the “21st Century Maritime Silk Road” (hereinafter referred to as the Belt and Road) was raised. To get a better understanding of “the Belt and Road” whole region, considering the large-scale characteristic, the Moon platform is a good choice. In this paper, the ephemeris is taken as data source and the positions and attitudes of Sun, Earth and Moon are obtained based on the reference systems transformation. Then we construct a simplified observation model and calculate the spatial and angular visibility of the Moon platform for “the Belt and Road” region. It turns out that Moon-based observation of this region shows a good performance of spatial visibility and variable angular visibility, indicating the Moon being a new potential platform for large-scale Earth observation.

Attribution of regional flood changes based on scaling fingerprints

NASA Astrophysics Data System (ADS)

Viglione, A.; Merz, B.; Dung, N.; Parajka, J.; Nester, T.; Bloeschl, G.

2017-12-01

Changes in the river flood regime may be due to atmospheric processes (e.g., increasing precipitation), catchment processes (e.g., soil compaction associated with land use change), and river system processes (e.g., loss of retention volume in the floodplains). We propose a framework for attributing flood changes to these drivers based on a regional analysis. We exploit the scaling characteristics (i.e., fingerprints) with catchment area of the effects of the drivers on flood changes. The estimation of their relative contributions is framed in Bayesian terms. Analysis of a synthetic, controlled case suggests that the accuracy of the regional attribution increases with increasing number of sites and record lengths, decreases with increasing regional heterogeneity, increases with increasing difference of the scaling fingerprints, and decreases with an increase of their prior uncertainty. The applicability of the framework is illustrated for a case study set in Austria, where positive flood trends have been observed at many sites in the past decades. The individual scaling fingerprints related to the atmospheric, catchment, and river system processes are estimated from rainfall data and simple hydrological modeling. Although the distributions of the contributions are rather wide, the attribution identifies precipitation change as the main driver of flood change in the study region.

Large Scale Processes and Extreme Floods in Brazil

NASA Astrophysics Data System (ADS)

Ribeiro Lima, C. H.; AghaKouchak, A.; Lall, U.

2016-12-01

Persistent large scale anomalies in the atmospheric circulation and ocean state have been associated with heavy rainfall and extreme floods in water basins of different sizes across the world. Such studies have emerged in the last years as a new tool to improve the traditional, stationary based approach in flood frequency analysis and flood prediction. Here we seek to advance previous studies by evaluating the dominance of large scale processes (e.g. atmospheric rivers/moisture transport) over local processes (e.g. local convection) in producing floods. We consider flood-prone regions in Brazil as case studies and the role of large scale climate processes in generating extreme floods in such regions is explored by means of observed streamflow, reanalysis data and machine learning methods. The dynamics of the large scale atmospheric circulation in the days prior to the flood events are evaluated based on the vertically integrated moisture flux and its divergence field, which are interpreted in a low-dimensional space as obtained by machine learning techniques, particularly supervised kernel principal component analysis. In such reduced dimensional space, clusters are obtained in order to better understand the role of regional moisture recycling or teleconnected moisture in producing floods of a given magnitude. The convective available potential energy (CAPE) is also used as a measure of local convection activities. We investigate for individual sites the exceedance probability in which large scale atmospheric fluxes dominate the flood process. Finally, we analyze regional patterns of floods and how the scaling law of floods with drainage area responds to changes in the climate forcing mechanisms (e.g. local vs large scale).

Attribution of regional flood changes based on scaling fingerprints

PubMed Central

Merz, Bruno; Viet Dung, Nguyen; Parajka, Juraj; Nester, Thomas; Blöschl, Günter

2016-01-01

Abstract Changes in the river flood regime may be due to atmospheric processes (e.g., increasing precipitation), catchment processes (e.g., soil compaction associated with land use change), and river system processes (e.g., loss of retention volume in the floodplains). This paper proposes a new framework for attributing flood changes to these drivers based on a regional analysis. We exploit the scaling characteristics (i.e., fingerprints) with catchment area of the effects of the drivers on flood changes. The estimation of their relative contributions is framed in Bayesian terms. Analysis of a synthetic, controlled case suggests that the accuracy of the regional attribution increases with increasing number of sites and record lengths, decreases with increasing regional heterogeneity, increases with increasing difference of the scaling fingerprints, and decreases with an increase of their prior uncertainty. The applicability of the framework is illustrated for a case study set in Austria, where positive flood trends have been observed at many sites in the past decades. The individual scaling fingerprints related to the atmospheric, catchment, and river system processes are estimated from rainfall data and simple hydrological modeling. Although the distributions of the contributions are rather wide, the attribution identifies precipitation change as the main driver of flood change in the study region. Overall, it is suggested that the extension from local attribution to a regional framework, including multiple drivers and explicit estimation of uncertainty, could constitute a similar shift in flood change attribution as the extension from local to regional flood frequency analysis. PMID:27609996

A Method for Estimating Noise from Full-Scale Distributed Exhaust Nozzles

NASA Technical Reports Server (NTRS)

Kinzie, Kevin W.; Schein, David B.

2004-01-01

A method to estimate the full-scale noise suppression from a scale model distributed exhaust nozzle (DEN) is presented. For a conventional scale model exhaust nozzle, Strouhal number scaling using a scale factor related to the nozzle exit area is typically applied that shifts model scale frequency in proportion to the geometric scale factor. However, model scale DEN designs have two inherent length scales. One is associated with the mini-nozzles, whose size do not change in going from model scale to full scale. The other is associated with the overall nozzle exit area which is much smaller than full size. Consequently, lower frequency energy that is generated by the coalesced jet plume should scale to lower frequency, but higher frequency energy generated by individual mini-jets does not shift frequency. In addition, jet-jet acoustic shielding by the array of mini-nozzles is a significant noise reduction effect that may change with DEN model size. A technique has been developed to scale laboratory model spectral data based on the premise that high and low frequency content must be treated differently during the scaling process. The model-scale distributed exhaust spectra are divided into low and high frequency regions that are then adjusted to full scale separately based on different physics-based scaling laws. The regions are then recombined to create an estimate of the full-scale acoustic spectra. These spectra can then be converted to perceived noise levels (PNL). The paper presents the details of this methodology and provides an example of the estimated noise suppression by a distributed exhaust nozzle compared to a round conic nozzle.

The development of estimated methodology for interfacial adhesion of semiconductor coatings having an enormous mismatch extent

NASA Astrophysics Data System (ADS)

Lee, Chang-Chun; Huang, Pei-Chen

2018-05-01

The long-term reliability of multi-stacked coatings suffering the bending or rolling load was a severe challenge to extend the lifespan of foregoing structure. In addition, the adhesive strength of dissimilar materials was regarded as the major mechanical reliability concerns among multi-stacked films. However, the significant scale-mismatch from several nano-meter to micro-meter among the multi-stacked coatings causing the numerical accuracy and converged capability issues on fracture-based simulation approach. For those reasons, this study proposed the FEA-based multi-level submodeling and multi-point constraint (MPC) technique to conquer the foregoing scale-mismatch issue. The results indicated that the decent region of first and second-order submodeling can achieve the small error of 1.27% compared with the experimental result and significantly reduced the mesh density and computing time. Moreover, the MPC method adopted in FEA simulation also shown only 0.54% error when the boundary of selected local region was away the concerned critical region following the Saint-Venant principle. In this investigation, two FEA-based approaches were used to conquer the evidently scale mismatch issue when the adhesive strengths of micro and nano-scale multi-stacked coating were taken into account.

Analysis of the temporal-spatial distribution of ionosphere scale height based on COSMIC occultation data

NASA Astrophysics Data System (ADS)

Ma, Xin-Xin; Lin, Zhan; Jin, Hong-Lin; Chen, Hua-Ran; Jiao, Li-Guo

2017-11-01

In this study, the distribution characteristics of scale height at various solar activity levels were statistically analyzed using the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation data for 2007-2013. The results show that: (1) in the mid-high latitude region, the daytime (06-17LT) scale height exhibits annual variations in the form of a single peak structure with the crest appearing in summer. At the high latitude region, an annual variation is also observed for nighttime (18-05LT) scale height; (2) changes in the spatial distribution of the scale height occur. The crests are deflected towards the north during daytime (12-14LT) at a geomagnetic longitude of 60°W-180°W, and they are distributed roughly along the geomagnetic equator at 60°W-180°E. In the approximate region of 120°W-150°E and 50°S-80°S, the scale height values are significantly higher than those in other mid-latitude areas. This region enlarges with increased solar activity, and shows an approximately symmetric distribution about 0° geomagnetic longitude. Nighttime (00-02LT) scale height values in the high-latitude region are larger than those in the low-mid latitude region. These results could serve as reference for the study of ionosphere distribution and construction of the corresponding profile model.

Can Regional Climate Models be used in the assessment of vulnerability and risk caused by extreme events?

NASA Astrophysics Data System (ADS)

Nunes, Ana

2015-04-01

Extreme meteorological events played an important role in catastrophic occurrences observed in the past over densely populated areas in Brazil. This motived the proposal of an integrated system for analysis and assessment of vulnerability and risk caused by extreme events in urban areas that are particularly affected by complex topography. That requires a multi-scale approach, which is centered on a regional modeling system, consisting of a regional (spectral) climate model coupled to a land-surface scheme. This regional modeling system employs a boundary forcing method based on scale-selective bias correction and assimilation of satellite-based precipitation estimates. Scale-selective bias correction is a method similar to the spectral nudging technique for dynamical downscaling that allows internal modes to develop in agreement with the large-scale features, while the precipitation assimilation procedure improves the modeled deep-convection and drives the land-surface scheme variables. Here, the scale-selective bias correction acts only on the rotational part of the wind field, letting the precipitation assimilation procedure to correct moisture convergence, in order to reconstruct South American current climate within the South American Hydroclimate Reconstruction Project. The hydroclimate reconstruction outputs might eventually produce improved initial conditions for high-resolution numerical integrations in metropolitan regions, generating more reliable short-term precipitation predictions, and providing accurate hidrometeorological variables to higher resolution geomorphological models. Better representation of deep-convection from intermediate scales is relevant when the resolution of the regional modeling system is refined by any method to meet the scale of geomorphological dynamic models of stability and mass movement, assisting in the assessment of risk areas and estimation of terrain stability over complex topography. The reconstruction of past extreme events also helps the development of a system for decision-making, regarding natural and social disasters, and reducing impacts. Numerical experiments using this regional modeling system successfully modeled severe weather events in Brazil. Comparisons with the NCEP Climate Forecast System Reanalysis outputs were made at resolutions of about 40- and 25-km of the regional climate model.

Regional and local species richness in an insular environment: Serpentine plants in California

USGS Publications Warehouse

Harrison, S.; Safford, H.D.; Grace, J.B.; Viers, J.H.; Davies, K.F.

2006-01-01

We asked how the richness of the specialized (endemic) flora of serpentine rock outcrops in California varies at both the regional and local scales. Our study had two goals: first, to test whether endemic richness is affected by spatial habitat structure (e.g., regional serpentine area, local serpentine outcrop area, regional and local measures of outcrop isolation), and second, to conduct this test in the context of a broader assessment of environmental influences (e.g., climate, soils, vegetation, disturbance) and historical influences (e.g., geologic age, geographic province) on local and regional species richness. We measured endemic and total richness and environmental variables in 109 serpentine sites (1000-m2 paired plots) in 78 serpentine-containing regions of the state. We used structural equation modeling (SEM) to simultaneously relate regional richness to regionalscale predictors, and local richness to both local-scale and regional-scale predictors. Our model for serpentine endemics explained 66% of the variation in local endemic richness based on local environment (vegetation, soils, rock cover) and on regional endemic richness. It explained 73% of the variation in regional endemic richness based on regional environment (climate and productivity), historical factors (geologic age and geographic province), and spatial structure (regional total area of serpentine, the only significant spatial variable in our analysis). We did not find a strong influence of spatial structure on species richness. However, we were able to distinguish local vs. regional influences on species richness to a novel extent, despite the existence of correlations between local and regional conditions. ?? 2006 by the Ecological Society of America.

A scale-invariant change detection method for land use/cover change research

NASA Astrophysics Data System (ADS)

Xing, Jin; Sieber, Renee; Caelli, Terrence

2018-07-01

Land Use/Cover Change (LUCC) detection relies increasingly on comparing remote sensing images with different spatial and spectral scales. Based on scale-invariant image analysis algorithms in computer vision, we propose a scale-invariant LUCC detection method to identify changes from scale heterogeneous images. This method is composed of an entropy-based spatial decomposition, two scale-invariant feature extraction methods, Maximally Stable Extremal Region (MSER) and Scale-Invariant Feature Transformation (SIFT) algorithms, a spatial regression voting method to integrate MSER and SIFT results, a Markov Random Field-based smoothing method, and a support vector machine classification method to assign LUCC labels. We test the scale invariance of our new method with a LUCC case study in Montreal, Canada, 2005-2012. We found that the scale-invariant LUCC detection method provides similar accuracy compared with the resampling-based approach but this method avoids the LUCC distortion incurred by resampling.

Correspondence between solar fine-scale structures in the corona, transition region, and lower atmosphere from collaborative observations

NASA Technical Reports Server (NTRS)

Moses, J. Daniel; Cook, J. W.; Bartoe, J.-D. F.; Brueckner, G. E.; Dere, K. P.; Webb, D. F.; Davis, John M.; Recely, F.; Martin, S. F.; Zirin, H.

1989-01-01

The Soft X-Ray Imaging Payload and the High Resolution Telescope and Spectrograph (HRTS) instrument were launched from White Sands on 11 December 1987 in coordinated sounding rocket flights to investigate the correspondence of coronal and transition region structures, especially the relationship between X-ray bright points (XBPs) and transition region small spatial scale energetic events. The coaligned data from X-ray images are presented along with maps of sites of transition region energetic events observed in C IV (100,000 K), HRTS 1600 A spectroheliograms of the T sub min region and ground based magnetogram and He I 10830 A images.

Parcels versus pixels: modeling agricultural land use across broad geographic regions using parcel-based field boundaries

USGS Publications Warehouse

Sohl, Terry L.; Dornbierer, Jordan; Wika, Steve; Sayler, Kristi L.; Quenzer, Robert

2017-01-01

Land use and land cover (LULC) change occurs at a local level within contiguous ownership and management units (parcels), yet LULC models primarily use pixel-based spatial frameworks. The few parcel-based models being used overwhelmingly focus on small geographic areas, limiting the ability to assess LULC change impacts at regional to national scales. We developed a modified version of the Forecasting Scenarios of land use change model to project parcel-based agricultural change across a large region in the United States Great Plains. A scenario representing an agricultural biofuel scenario was modeled from 2012 to 2030, using real parcel boundaries based on contiguous ownership and land management units. The resulting LULC projection provides a vastly improved representation of landscape pattern over existing pixel-based models, while simultaneously providing an unprecedented combination of thematic detail and broad geographic extent. The conceptual approach is practical and scalable, with potential use for national-scale projections.

Detecting and analyzing soil phosphorus loss associated with critical source areas using a remote sensing approach.

PubMed

Lou, Hezhen; Yang, Shengtian; Zhao, Changsen; Shi, Liuhua; Wu, Linna; Wang, Yue; Wang, Zhiwei

2016-12-15

The detection of critical source areas (CSAs) is a key step in managing soil phosphorus (P) loss and preventing the long-term eutrophication of water bodies at regional scale. Most related studies, however, focus on a local scale, which prevents a clear understanding of the spatial distribution of CSAs for soil P loss at regional scale. Moreover, the continual, long-term variation in CSAs was scarcely reported. It is impossible to identify the factors driving the variation in CSAs, or to collect land surface information essential for CSAs detection, by merely using the conventional methodologies at regional scale. This study proposes a new regional-scale approach, based on three satellite sensors (ASTER, TM/ETM and MODIS), that were implemented successfully to detect CSAs at regional scale over 15years (2000-2014). The approach incorporated five factors (precipitation, slope, soil erosion, land use, soil total phosphorus) that drive soil P loss from CSAs. Results show that the average area of critical phosphorus source areas (CPSAs) was 15,056km 2 over the 15-year period, and it occupied 13.8% of the total area, with a range varying from 1.2% to 23.0%, in a representative, intensive agricultural area of China. In contrast to previous studies, we found that the locations of CSAs with P loss are spatially variable, and are more dispersed in their distribution over the long term. We also found that precipitation acts as a key driving factor in the variation of CSAs at regional scale. The regional-scale method can provide scientific guidance for managing soil phosphorus loss and preventing the long-term eutrophication of water bodies at regional scale, and shows great potential for exploring factors that drive the variation in CSAs at global scale. Copyright © 2016 Elsevier B.V. All rights reserved.

Cloud-based computation for accelerating vegetation mapping and change detection at regional to national scales

Treesearch

Matthew J. Gregory; Zhiqiang Yang; David M. Bell; Warren B. Cohen; Sean Healey; Janet L. Ohmann; Heather M. Roberts

2015-01-01

Mapping vegetation and landscape change at fine spatial scales is needed to inform natural resource and conservation planning, but such maps are expensive and time-consuming to produce. For Landsat-based methodologies, mapping efforts are hampered by the daunting task of manipulating multivariate data for millions to billions of pixels. The advent of cloud-based...

REGIONAL VULNERABILITY: A CONCEPTUAL FRAMEWORK

EPA Science Inventory

Regional vulnerability assessment, or ReVA, is an approach to place-based ecological risk assessment that is currently under development by the Office of Research and Development of the U.S. Environmental Protection Agency (EPA). The assessment is done at the scale of EPA region...

Use of Multi-Year MODIS Phenological Data Products to Detect and Monitor Forest Disturbances at Regional and National Scales

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William W.; Gasser, Jerry; Smoot, James; Ross, Kenton

2010-01-01

This presentation discusses an effort to use select MODIS phenological products for forest disturbance monitoring at the regional and CONUS scales. Forests occur on 1/3 of the U.S. land base and include regionally prevalent forest disturbances that can threaten forest sustainability. Regional and CONUS forest disturbance monitoring is needed for a national forest threat early warning system being developed by the USDA Forest Service with help from NASA, ORNL, and USGS. MODIS NDVI phenology products are being used to develop forest disturbance monitoring capabilities of this EWS.

Long-term hydrometeorological trends in the Midwest region based on a century long gridded hydrometeorological dataset and simulations from a macro-scale hydrology model

NASA Astrophysics Data System (ADS)

Chiu, C. M.; Hamlet, A. F.

2014-12-01

Climate change is likely to impact the Great Lakes region and Midwest region via changes in Great Lakes water levels, agricultural impacts, river flooding, urban stormwater impacts, drought, water temperature, and impacts to terrestrial and aquatic ecosystems. Self-consistent and temporally homogeneous long-term data sets of precipitation and temperature over the entire Great Lakes region and Midwest regions are needed to provide inputs to hydrologic models, assess historical trends in hydroclimatic variables, and downscale global and regional-scale climate models. To support these needs a new hybrid gridded meteorological forcing dataset at 1/16 degree resolution based on data from co-op station records, the U. S Historical Climatology Network (HCN) , the Historical Canadian Climate Database (HCCD), and Precipitation Regression on Independent Slopes Method (PRISM) has been assembled over the Great Lakes and Midwest region from 1915-2012 at daily time step. These data were then used as inputs to the macro-scale Variable Infiltration Capacity (VIC) hydrology model, implemented over the Midwest and Great Lakes region at 1/16 degree resolution, to produce simulated hydrologic variables that are amenable to long-term trend analysis. Trends in precipitation and temperature from the new meteorological driving data sets, as well as simulated hydrometeorological variables such as snowpack, soil moisture, runoff, and evaporation over the 20th century are presented and discussed.

Assessing Regional Scale Fluxes of Mass, Momentum, and Energy with Small Environmental Research Aircraft

NASA Astrophysics Data System (ADS)

Zulueta, Rommel Callejo

Natural ecosystems are rarely structurally or functionally homogeneous. This is true for the complex coastal regions of Magdalena Bay, Baja California Sur, Mexico, and the Barrow Peninsula on the Arctic Coastal Plain of Alaska. The coastal region of Magdalena Bay is comprised of the Pacific coastal ocean, eutrophic lagoon, mangroves, and desert ecosystems all adjacent and within a few kilometers, while the Barrow Peninsula is a mosaic of small ponds, thaw lakes, different aged vegetated thaw-lake basins ( VDTLBs ) and interstitial tundra which have been dynamically formed by both short- and long-term processes. We used a combination of tower- and small environmental research aircraft (SERA)-based eddy covariance measurements to characterize the spatial and temporal patterns of CO2, latent, and sensible heat fluxes along with MODIS NDVI, and land surface information, to scale the SERA-based CO2 fluxes up to the regional scale. In the first part of this research, the spatial variability in ecosystem fluxes from the Pacific coastal ocean, eutrophic lagoon, mangroves, and desert areas of northern Magdalena Bay were studied. SERA-derived average midday CO2 fluxes from the desert showed a slight uptake of -1.32 mumol CO2 m-2 s-1, the coastal ocean also showed uptake of -3.48 mumol CO2 m-2 s -1, and the lagoon mangroves showed the highest uptake of -8.11 mumol CO2 m-2 s-1. Additional simultaneous measurements of NDVI allowed simple linear modeling of CO2 flux as a function of NDVI for the mangroves of the Magdalena Bay region. In the second part of this research, the spatial variability of ecosystem fluxes across the 1802 km2 Barrow Peninsula region was studied. During typical 2006 summer conditions, the midday hourly CO2 flux over the region was -2.04 x 105 kgCO2 hr-1. The CO2 fluxes among the interstitial tundra, Ancient and Old VDTLBs, as well as between the Medium and Young VDTLBs were not significantly different. Combined, the interstitial tundra and Old and Ancient VDTLBs, represent ˜67% of the Barrow Peninsula surface area, accounting for ˜59% of the regional flux signal. Though the Medium and Young VDTLBs represent ˜11% of the surface area, they account for a large portion, ˜35%, of the total regional flux. The remaining ˜22% of the surface area are lakes and contributed the remaining ˜6% of the total regional flux. Previous studies treated vegetated areas of the region as a single surface type with measurements from a few study sites; doing so could underestimate the regional flux by ˜22%. The San Diego State University Sky Arrow 650TCN Environmental Research Aircraft proved to be an effective tool in characterizing land-atmosphere fluxes of energy, CO2 and water across heterogeneous landscapes at the scale of 1 km, and was capable of discriminating fluxes from the various ecosystem and land surface types a few kilometers distant. Here, we demonstrate that SERA-based approaches have the ability to cover large spatial scales while measuring the turbulent fluxes across a number of surfaces and combined with ground- and satellite-based measurements provide a valuable tool for both scaling and validation of regional-scale fluxes.

The consequences of landscape change on ecological resources: An assessment of the United States Mid-Atlantic region, 1973-1993

Treesearch

K. Bruce Jones; Anne C. Neale; Timothy G. Wade; James D. Wickham; Chad L. Cross; Curtis M. Edmonds; Thomas R. Loveland; Maliha S. Nash; Kurt H. Riitters; Elizabeth R. Smith

2001-01-01

Spatially explicit identification of changes in ecological conditions over large areas is key to targeting and prioitizing areas for environmental protection and restoration by managers at watershed, basin, and regional scales. A critical limitation to this point has been the development of methods to conduct such broad-scale assessments. Field-based methods have...

Derivation of Zagarola-Smits scaling in zero-pressure-gradient turbulent boundary layers

NASA Astrophysics Data System (ADS)

Wei, Tie; Maciel, Yvan

2018-01-01

This Rapid Communication derives the Zagarola-Smits scaling directly from the governing equations for zero-pressure-gradient turbulent boundary layers (ZPG TBLs). It has long been observed that the scaling of the mean streamwise velocity in turbulent boundary layer flows differs in the near surface region and in the outer layer. In the inner region of small-velocity-defect boundary layers, it is generally accepted that the proper velocity scale is the friction velocity, uτ, and the proper length scale is the viscous length scale, ν /uτ . In the outer region, the most generally used length scale is the boundary layer thickness, δ . However, there is no consensus on velocity scales in the outer layer. Zagarola and Smits [ASME Paper No. FEDSM98-4950 (1998)] proposed a velocity scale, U ZS=(δ1/δ ) U∞ , where δ1 is the displacement thickness and U∞ is the freestream velocity. However, there are some concerns about Zagarola-Smits scaling due to the lack of a theoretical base. In this paper, the Zagarola-Smits scaling is derived directly from a combination of integral, similarity, and order-of-magnitude analysis of the mean continuity equation. The analysis also reveals that V∞, the mean wall-normal velocity at the edge of the boundary layer, is a proper scale for the mean wall-normal velocity V . Extending the analysis to the streamwise mean momentum equation, we find that the Reynolds shear stress in ZPG TBLs scales as U∞V∞ in the outer region. This paper also provides a detailed analysis of the mass and mean momentum balance in the outer region of ZPG TBLs.

Verification of GCM-generated regional seasonal precipitation for current climate and of statistical downscaling estimates under changing climate conditions

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

Busuioc, A.; Storch, H. von; Schnur, R.

Empirical downscaling procedures relate large-scale atmospheric features with local features such as station rainfall in order to facilitate local scenarios of climate change. The purpose of the present paper is twofold: first, a downscaling technique is used as a diagnostic tool to verify the performance of climate models on the regional scale; second, a technique is proposed for verifying the validity of empirical downscaling procedures in climate change applications. The case considered is regional seasonal precipitation in Romania. The downscaling model is a regression based on canonical correlation analysis between observed station precipitation and European-scale sea level pressure (SLP). Themore » climate models considered here are the T21 and T42 versions of the Hamburg ECHAM3 atmospheric GCM run in time-slice mode. The climate change scenario refers to the expected time of doubled carbon dioxide concentrations around the year 2050. Generally, applications of statistical downscaling to climate change scenarios have been based on the assumption that the empirical link between the large-scale and regional parameters remains valid under a changed climate. In this study, a rationale is proposed for this assumption by showing the consistency of the 2 x CO{sub 2} GCM scenarios in winter, derived directly from the gridpoint data, with the regional scenarios obtained through empirical downscaling. Since the skill of the GCMs in regional terms is already established, it is concluded that the downscaling technique is adequate for describing climatically changing regional and local conditions, at least for precipitation in Romania during winter.« less

Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity.

PubMed

Wang, Danny J J; Jann, Kay; Fan, Chang; Qiao, Yang; Zang, Yu-Feng; Lu, Hanbing; Yang, Yihong

2018-01-01

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of electrophysiology and fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). MSE and FC analyses were performed on simulated data using neural mass model based brain network model with the Brain Dynamics Toolbox, on animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations, and on resting-state fMRI data from the Human Connectome Project. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC. The associations between MSE and FC are dependent on the temporal scales or frequencies, with higher associations between MSE and FC at lower temporal frequencies. Our results from theoretical modeling, animal experiment and human fMRI indicate that (1) Regional neural complexity and network FC may be two related aspects of brain's information processing: the more complex regional neural activity, the higher FC this region has with other brain regions; (2) MSE at high and low frequencies may represent local and distributed information processing across brain regions. Based on literature and our data, we propose that the complexity of regional neural signals may serve as an index of the brain's capacity of information processing-increased complexity may indicate greater transition or exploration between different states of brain networks, thereby a greater propensity for information processing.

Analysis of surface scale on the Ni-based superalloy CMSX-10N and proposed mechanism of formation

NASA Astrophysics Data System (ADS)

Simmonds, S.; D'Souza, N.; Ryder, K. S.; Dong, H.

2012-01-01

There is a continuing demand to raise the operating temperature of jet engine turbine blades to meet the need for higher turbine entry temperatures (TET) in order to increase thermal efficiency and thrust. Modern, high-pressure turbine blades are made from Ni-based superalloys in single-crystal form via the investment casting process. One important post-cast surface defect, known as 'surface scale', has been investigated on the alloy CMSX-10N. This is an area of distinct discolouration of the aerofoil seen after casting. Auger electron and X-ray photoelectron spectroscopy analysis were carried out on both scaled and un-scaled areas. In the scaled region, a thin layer (~800nm) of Ni oxide is evident. In the un-scaled regions there is a thicker Al2O3 layer. It is shown that, as the blade cools during casting, differential thermal contraction of mould and alloy causes the solid blade to 'detach' from the mould in these scaled areas. The formation of Ni Oxides is facilitated by this separation.

Analysis of the Effect of Interior Nudging on Temperature and Precipitation Distributions of Multi-year Regional Climate Simulations

NASA Astrophysics Data System (ADS)

Nolte, C. G.; Otte, T. L.; Bowden, J. H.; Otte, M. J.

2010-12-01

There is disagreement in the regional climate modeling community as to the appropriateness of the use of internal nudging. Some investigators argue that the regional model should be minimally constrained and allowed to respond to regional-scale forcing, while others have noted that in the absence of interior nudging, significant large-scale discrepancies develop between the regional model solution and the driving coarse-scale fields. These discrepancies lead to reduced confidence in the ability of regional climate models to dynamically downscale global climate model simulations under climate change scenarios, and detract from the usability of the regional simulations for impact assessments. The advantages and limitations of interior nudging schemes for regional climate modeling are investigated in this study. Multi-year simulations using the WRF model driven by reanalysis data over the continental United States at 36km resolution are conducted using spectral nudging, grid point nudging, and for a base case without interior nudging. The means, distributions, and inter-annual variability of temperature and precipitation will be evaluated in comparison to regional analyses.

Multi-scaling allometric analysis for urban and regional development

NASA Astrophysics Data System (ADS)

Chen, Yanguang

2017-01-01

The concept of allometric growth is based on scaling relations, and it has been applied to urban and regional analysis for a long time. However, most allometric analyses were devoted to the single proportional relation between two elements of a geographical system. Few researches focus on the allometric scaling of multielements. In this paper, a process of multiscaling allometric analysis is developed for the studies on spatio-temporal evolution of complex systems. By means of linear algebra, general system theory, and by analogy with the analytical hierarchy process, the concepts of allometric growth can be integrated with the ideas from fractal dimension. Thus a new methodology of geo-spatial analysis and the related theoretical models emerge. Based on the least squares regression and matrix operations, a simple algorithm is proposed to solve the multiscaling allometric equation. Applying the analytical method of multielement allometry to Chinese cities and regions yields satisfying results. A conclusion is reached that the multiscaling allometric analysis can be employed to make a comprehensive evaluation for the relative levels of urban and regional development, and explain spatial heterogeneity. The notion of multiscaling allometry may enrich the current theory and methodology of spatial analyses of urban and regional evolution.

New methods of MR image intensity standardization via generalized scale

NASA Astrophysics Data System (ADS)

Madabhushi, Anant; Udupa, Jayaram K.

2005-04-01

Image intensity standardization is a post-acquisition processing operation designed for correcting acquisition-to-acquisition signal intensity variations (non-standardness) inherent in Magnetic Resonance (MR) images. While existing standardization methods based on histogram landmarks have been shown to produce a significant gain in the similarity of resulting image intensities, their weakness is that, in some instances the same histogram-based landmark may represent one tissue, while in other cases it may represent different tissues. This is often true for diseased or abnormal patient studies in which significant changes in the image intensity characteristics may occur. In an attempt to overcome this problem, in this paper, we present two new intensity standardization methods based on the concept of generalized scale. In reference 1 we introduced the concept of generalized scale (g-scale) to overcome the shape, topological, and anisotropic constraints imposed by other local morphometric scale models. Roughly speaking, the g-scale of a voxel in a scene was defined as the largest set of voxels connected to the voxel that satisfy some homogeneity criterion. We subsequently formulated a variant of the generalized scale notion, referred to as generalized ball scale (gB-scale), which, in addition to having the advantages of g-scale, also has superior noise resistance properties. These scale concepts are utilized in this paper to accurately determine principal tissue regions within MR images, and landmarks derived from these regions are used to perform intensity standardization. The new methods were qualitatively and quantitatively evaluated on a total of 67 clinical 3D MR images corresponding to four different protocols and to normal, Multiple Sclerosis (MS), and brain tumor patient studies. The generalized scale-based methods were found to be better than the existing methods, with a significant improvement observed for severely diseased and abnormal patient studies.

Advances in Landslide Nowcasting: Evaluation of a Global and Regional Modeling Approach

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia Bach; Peters-Lidard, Christa; Adler, Robert; Hong, Yang; Kumar, Sujay; Lerner-Lam, Arthur

2011-01-01

The increasing availability of remotely sensed data offers a new opportunity to address landslide hazard assessment at larger spatial scales. A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that may experience landslide activity. This system combines a calculation of static landslide susceptibility with satellite-derived rainfall estimates and uses a threshold approach to generate a set of nowcasts that classify potentially hazardous areas. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale near real-time landslide hazard assessment efforts, it requires several modifications before it can be fully realized as an operational tool. This study draws upon a prior work s recommendations to develop a new approach for considering landslide susceptibility and hazard at the regional scale. This case study calculates a regional susceptibility map using remotely sensed and in situ information and a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America. The susceptibility map is evaluated with a regional rainfall intensity duration triggering threshold and results are compared with the global algorithm framework for the same event. Evaluation of this regional system suggests that this empirically based approach provides one plausible way to approach some of the data and resolution issues identified in the global assessment. The presented methodology is straightforward to implement, improves upon the global approach, and allows for results to be transferable between regions. The results also highlight several remaining challenges, including the empirical nature of the algorithm framework and adequate information for algorithm validation. Conclusions suggest that integrating additional triggering factors such as soil moisture may help to improve algorithm performance accuracy. The regional algorithm scenario represents an important step forward in advancing regional and global-scale landslide hazard assessment.

Varying Herbivore Population Structure Correlates with Lack of Local Adaptation in a Geographic Variable Plant-Herbivore Interaction

PubMed Central

Cogni, Rodrigo; Trigo, José R.; Futuyma, Douglas J.

2011-01-01

Local adaptation of parasites to their hosts due to coevolution is a central prediction of many theories in evolutionary biology. However, empirical studies looking for parasite local adaptation show great variation in outcomes, and the reasons for such variation are largely unknown. In a previous study, we showed adaptive differentiation in the arctiid moth Utetheisa ornatrix to its host plant, the pyrrolizidine alkaloid-bearing legume Crotalaria pallida, at the continental scale, but found no differentiation at the regional scale. In the present study, we sampled the same sites to investigate factors that may contribute to the lack of differentiation at the regional scale. We performed field observations that show that specialist and non-specialist polyphagous herbivore incidence varies among populations at both scales. With a series of common-garden experiments we show that some plant traits that may affect herbivory (pyrrolizidine alkaloids and extrafloral nectaries) vary at the regional scale, while other traits (trichomes and nitrogen content) just vary at the continental scale. These results, combined with our previous evidence for plant population differentiation based on larval performance on fresh fruits, suggest that U. ornatrix is subjected to divergent selection even at the regional scale. Finally, with a microsatellite study we investigated population structure of U. ornatrix. We found that population structure is not stable over time: we found population differentiation at the regional scale in the first year of sampling, but not in the second year. Unstable population structure of the herbivore is the most likely cause of the lack of regional adaptation. PMID:22220208

Insight on invasions and resilience derived from spatiotemporal discontinuities of biomass at local and regional scales

USGS Publications Warehouse

Angeler, David G.; Allen, Criag R.; Johnson, Richard K.

2012-01-01

Understanding the social and ecological consequences of species invasions is complicated by nonlinearities in processes, and differences in process and structure as scale is changed. Here we use discontinuity analyses to investigate nonlinear patterns in the distribution of biomass of an invasive nuisance species that could indicate scale-specific organization. We analyze biomass patterns in the flagellate Gonyostomum semen (Raphidophyta) in 75 boreal lakes during an 11-year period (1997-2007). With simulations using a unimodal null model and cluster analysis, we identified regional groupings of lakes based on their biomass patterns. We evaluated the variability of membership of individual lakes in regional biomass groups. Temporal trends in local and regional discontinuity patterns were analyzed using regressions and correlations with environmental variables that characterize nutrient conditions, acidity status, temperature variability, and water clarity. Regionally, there was a significant increase in the number of biomass groups over time, indicative of an increased number of scales at which algal biomass organizes across lakes. This increased complexity correlated with the invasion history of G. semen and broad-scale environmental change (recovery from acidification). Locally, no consistent patterns of lake membership to regional biomass groups were observed, and correlations with environmental variables were lake specific. The increased complexity of regional biomass patterns suggests that processes that act within or between scales reinforce the presence of G. semen and its potential to develop high-biomass blooms in boreal lakes. Emergent regional patterns combined with locally stochastic dynamics suggest a bleak future for managing G. semen, and more generally why invasive species can be ecologically successful.

The sense and non-sense of plot-scale, catchment-scale, continental-scale and global-scale hydrological modelling

NASA Astrophysics Data System (ADS)

Bronstert, Axel; Heistermann, Maik; Francke, Till

2017-04-01

Hydrological models aim at quantifying the hydrological cycle and its constituent processes for particular conditions, sites or periods in time. Such models have been developed for a large range of spatial and temporal scales. One must be aware that the question which is the appropriate scale to be applied depends on the overall question under study. Therefore, it is not advisable to give a general applicable guideline on what is "the best" scale for a model. This statement is even more relevant for coupled hydrological, ecological and atmospheric models. Although a general statement about the most appropriate modelling scale is not recommendable, it is worth to have a look on what are the advantages and the shortcomings of micro-, meso- and macro-scale approaches. Such an appraisal is of increasing importance, since increasingly (very) large / global scale approaches and models are under operation and therefore the question arises how far and for what purposes such methods may yield scientifically sound results. It is important to understand that in most hydrological (and ecological, atmospheric and other) studies process scale, measurement scale, and modelling scale differ from each other. In some cases, the differences between theses scales can be of different orders of magnitude (example: runoff formation, measurement and modelling). These differences are a major source of uncertainty in description and modelling of hydrological, ecological and atmospheric processes. Let us now summarize our viewpoint of the strengths (+) and weaknesses (-) of hydrological models of different scales: Micro scale (e.g. extent of a plot, field or hillslope): (+) enables process research, based on controlled experiments (e.g. infiltration; root water uptake; chemical matter transport); (+) data of state conditions (e.g. soil parameter, vegetation properties) and boundary fluxes (e.g. rainfall or evapotranspiration) are directly measurable and reproducible; (+) equations based on first principals, partly pde-type, are available for several processes (but not for all), because measurement and modelling scale are compatible (-) the spatial model domain are hardly representative for larger spatial entities, including regions for which water resources management decisions are to be taken; straightforward upsizing is also limited by data availability and computational requirements. Meso scale (e.g. extent of a small to large catchment or region): (+) the spatial extent of the model domain has approximately the same extent as the regions for which water resources management decisions are to be taken. I.e., such models enable water resources quantification at the scale of most water management decisions; (+) data of some state conditions (e.g. vegetation cover, topography, river network and cross sections) are available; (+) data of some boundary fluxes (in particular surface runoff / channel flow) are directly measurable with mostly sufficient certainty; (+) equations, partly based on simple water budgeting, partly variants of pde-type equations, are available for most hydrological processes. This enables the construction of meso-scale distributed models reflecting the spatial heterogeneity of regions/landscapes; (-) process scale, measurement scale, and modelling scale differ from each other for a number of processes, e.g., such as runoff generation; (-) the process formulation (usually derived from micro-scale studies) cannot directly be transferred to the modelling domain. Upscaling procedures for this purpose are not readily and generally available. Macro scale (e.g. extent of a continent up to global): (+) the spatial extent of the model may cover the whole Earth. This enables an attractive global display of model results; (+) model results might be technically interchangeable or at least comparable with results from other global models, such as global climate models; (-) process scale, measurement scale, and modelling scale differ heavily from each other for all hydrological and associated processes; (-) the model domain and its results are not representative regions for which water resources management decisions are to be taken. (-) both state condition and boundary flux data are hardly available for the whole model domain. Water management data and discharge data from remote regions are particular incomplete / unavailable for this scale. This undermines the model's verifiability; (-) since process formulation and resulting modelling reliability at this scale is very limited, such models can hardly show any explanatory skills or prognostic power; (-) since both the entire model domain and the spatial sub-units cover large areas, model results represent values averaged over at least the spatial sub-unit's extent. In many cases, the applied time scale implies a long-term averaging in time, too. We emphasize the importance to be aware of the above mentioned strengths and weaknesses of those scale-specific models. (Many of the) results of the current global model studies do not reflect such limitations. In particular, we consider the averaging over large model entities in space and/or time inadequate. Many hydrological processes are of a non-linear nature, including threshold-type behaviour. Such features cannot be reflected by such large scale entities. The model results therefore can be of little or no use for water resources decisions and/or even misleading for public debates or decision making. Some rather newly developed sustainability concepts, e.g. "Planetary Boundaries" in which humanity may "continue to develop and thrive for generations to come" are based on such global-scale approaches and models. However, many of the major problems regarding sustainability on Earth, e.g. water scarcity, do not exhibit on a global but on a regional scale. While on a global scale water might look like being available in sufficient quantity and quality, there are many regions where water problems already have very harmful or even devastating effects. Therefore, it is the challenge to derive models and observation programmes for regional scales. In case a global display is desired future efforts should be directed towards the development of a global picture based on a mosaic of regional sound assessments, rather than "zooming into" the results of large-scale simulations. Still, a key question remains to be discussed, i.e. for which purpose models at this (global) scale can be used.

Controls on mineralisation in the Sierra Foothills gold province, central California, USA: A GIS-based reconnaissance prospectivity analysis

USGS Publications Warehouse

Bierlein, F.P.; Northover, H.J.; Groves, D.I.; Goldfarb, R.J.; Marsh, E.E.

2008-01-01

The assessment of spatial relationships between the location, abundance and size of orogenic-gold deposits in the highly endowed Sierra Foothills gold province in California, via the combination of field studies and a GIS-based analysis, illustrates the power of such an approach to the characterisation of important parameters of mineral systems, and the prediction of districts likely to host economic mineralisation. Regional- to deposit-scale reconnaissance mapping suggests that deposition of gold-bearing quartz veins occurred in second- and third-order, east-over-west thrusts during regional east - west compression and right-lateral transpression. At the district-scale, significant zones of mineralisation correspond with such transpressional reactivation zones and dilational jogs that developed during the Late Jurassic - Early Cretaceous along the misaligned segments of first-order faults throughout the Sierra Nevada Foothills Metamorphic Belt. Field-based observations and interpretation of GIS data (including solid geology, structural elements, deposit locations, magnetics, gravity) also highlight the importance of structural permeability contrasts, rheological gradients, and variations in fault orientation for localising mineralisation. Although this approach confirms empirical findings and produces promising results at the province scale, enhanced geological, structural, geophysical and geochronological data density is required to generate regionally consistent, high-quality input layers that improve predictive targeting at the goldfield to deposit-scale.

An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs

NASA Astrophysics Data System (ADS)

Haaf, Ezra; Barthel, Roland

2016-04-01

When assessing hydrogeological conditions at the regional scale, the analyst is often confronted with uncertainty of structures, inputs and processes while having to base inference on scarce and patchy data. Haaf and Barthel (2015) proposed a concept for handling this predicament by developing a groundwater systems classification framework, where information is transferred from similar, but well-explored and better understood to poorly described systems. The concept is based on the central hypothesis that similar systems react similarly to the same inputs and vice versa. It is conceptually related to PUB (Prediction in ungauged basins) where organization of systems and processes by quantitative methods is intended and used to improve understanding and prediction. Furthermore, using the framework it is expected that regional conceptual and numerical models can be checked or enriched by ensemble generated data from neighborhood-based estimators. In a first step, groundwater hydrographs from a large dataset in Southern Germany are compared in an effort to identify structural similarity in groundwater dynamics. A number of approaches to group hydrographs, mostly based on a similarity measure - which have previously only been used in local-scale studies, can be found in the literature. These are tested alongside different global feature extraction techniques. The resulting classifications are then compared to a visual "expert assessment"-based classification which serves as a reference. A ranking of the classification methods is carried out and differences shown. Selected groups from the classifications are related to geological descriptors. Here we present the most promising results from a comparison of classifications based on series correlation, different series distances and series features, such as the coefficients of the discrete Fourier transform and the intrinsic mode functions of empirical mode decomposition. Additionally, we show examples of classes corresponding to geological descriptors. Haaf, E., Barthel, R., 2015. Methods for assessing hydrogeological similarity and for classification of groundwater systems on the regional scale, EGU General Assembly 2015, Vienna, Austria.

Assessment of regional climate change and development of climate adaptation decision aids in the Southwestern US

NASA Astrophysics Data System (ADS)

Darmenova, K.; Higgins, G.; Kiley, H.; Apling, D.

2010-12-01

Current General Circulation Models (GCMs) provide a valuable estimate of both natural and anthropogenic climate changes and variability on global scales. At the same time, future climate projections calculated with GCMs are not of sufficient spatial resolution to address regional needs. Many climate impact models require information at scales of 50 km or less, so dynamical downscaling is often used to estimate the smaller-scale information based on larger scale GCM output. To address current deficiencies in local planning and decision making with respect to regional climate change, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model and developing decision aids that translate the regional climate data into actionable information for users. Our methodology involves development of climatological indices of extreme weather and heating/cooling degree days based on WRF ensemble runs initialized with the NCEP-NCAR reanalysis and the European Center/Hamburg Model (ECHAM5). Results indicate that the downscale simulations provide the necessary detailed output required by state and local governments and the private sector to develop climate adaptation plans. In addition we evaluated the WRF performance in long-term climate simulations over the Southwestern US and validated against observational datasets.

REGIONAL AND STATE VIEWS OF ESTUARINE CONDITION IN NORTHEASTERN UNITED STATE BASED ON 2001 AND 2001 NATIONAL COASTAL ASSESSMENT DATA

EPA Science Inventory

The National Coastal Assessment (NCA) is a probability-based survey that permits assessment of estuarine conditions at national, regional, or large-system scales. Additionally, states may use these data to comply with requirements of the Clean Water Act (CWA), which mandates re...

REGIONAL AND STATE VIEWS OF ESTURAINE CONDITION IN NORTHEAST US BASED ON 2000 AND 2001 COASTAL ASSESSMENT DATA

EPA Science Inventory

The National Coastal Assessment (NCA) is a probability-based survey that permits assessment of estuarine conditions at national, regional, or large-system scales. Additionally, states may use these data to comply with requirements of the Clean Water Act (CWA), which mandates re...

Physiographic map of the Sicilian region (1:250,000 scale)

NASA Astrophysics Data System (ADS)

Priori, Simone; Fantappiè, Maria; Costantini, Edoardo A. C.

2015-04-01

Physiographic maps summarize and group the landforms of a territory into homogeneous areas in terms of kind and intensity of main geomorphological process. Most of the physiographic maps have large scale, which is national or continental scale. Other maps have been produced at the semi-detailed scales, while examples at the regional scale are much less common. However, being the Region the main administrative level in Europe, they can be very useful for land planning in many fields, such as ecological studies, risk maps, and soil mapping. This work presents a methodological example of regional physiographic map, compiled at 1:250,000 scale, representing the whole Sicilian region, the largest and most characteristic of Mediterranean island. The physiographic units were classed matching thematich layers (NDVI, geology, DEM, land cover) with the main geomorphological processes that were identified by stereo-interpretation of aerial photographs (1:70,000 scale). In addition, information from other published maps, representing geomorphological forms, aeolian deposits, anthropic terraced slopes, and landslide were used to improve the accuracy and reliability of the map. The classification of the physiographic units, and then the map legend, was built up on the basis of literature and taking into account Italian geomorphological legend. The legend proposed in this map, which can be applied also in other Mediterranean countries, is suitable for different scales. The landform units were grouped on the base of a geomorphological classification of the forms into: anthropogenic, eolian, coastal, valley floor, intermountain fluvial, slope erosional, structural, karstic, and volcanic.

Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods

NASA Astrophysics Data System (ADS)

He, Jiayi; Shang, Pengjian; Xiong, Hui

2018-06-01

Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.

A Review of International Large-Scale Assessments in Education: Assessing Component Skills and Collecting Contextual Data. PISA for Development

ERIC Educational Resources Information Center

Cresswell, John; Schwantner, Ursula; Waters, Charlotte

2015-01-01

This report reviews the major international and regional large-scale educational assessments, including international surveys, school-based surveys and household-based surveys. The report compares and contrasts the cognitive and contextual data collection instruments and implementation methods used by the different assessments in order to identify…

1:6000 Scale (6K) Quadrangles developed by USEPA to Support Reconnaissance, and Tactical and Strategic Planning for Emergency Responses and Homeland Security Events (Region 9 Extract)

EPA Pesticide Factsheets

Reference quads for emergency response reconnaissance developed for use by the US Environmental Protection Agency. Grid cells are based on densification of the USGS Quarterquad (1:12,000 scale or 12K) grids for the continental United States, Alaska, Hawaii and Puerto Rico and are roughly equivalent to 1:6000 scale (6K) quadrangles approximately 2 miles long on each side. Note: This file is a regional subset that has been extracted from a national file 6K quad file. Each regional extract includes a 20 mile buffer of tiles around each EPA Region. To access the national layer (size is greater than 80MB), go to https://edg.epa.gov/data/Public/OLEM/6kquads_epa.zip.

A new method for detecting, quantifying and monitoring diffuse contamination

NASA Astrophysics Data System (ADS)

Fabian, Karl; Reimann, Clemens; de Caritat, Patrice

2017-04-01

A new method is presented for detecting and quantifying diffuse contamination at the regional to continental scale. It is based on the analysis of cumulative distribution functions (CDFs) in cumulative probability (CP) plots for spatially representative datasets, preferably containing >1000 samples. Simulations demonstrate how different types of contamination influence elemental CDFs of different sample media. Contrary to common belief, diffuse contamination does not result in exceedingly high element concentrations in regional- to continental-scale datasets. Instead it produces a distinctive shift of concentrations in the background distribution of the studied element resulting in a steeper data distribution in the CP plot. Via either (1) comparing the distribution of an element in top soil samples to the distribution of the same element in bottom soil samples from the same area, taking soil forming processes into consideration, or (2) comparing the distribution of the contaminating element (e.g., Pb) to that of an element with a geochemically comparable behaviour but no contamination source (e.g., Rb or Ba in case of Pb), the relative impact of diffuse contamination on the element concentration can be estimated either graphically in the CP plot via a best fit estimate or quantitatively via a Kolmogorov-Smirnov or Cramer vonMiese test. This is demonstrated using continental-scale geochemical soil datasets from Europe, Australia, and the USA, and a regional scale dataset from Norway. Several different datasets from Europe deliver comparable results at regional to continental scales. The method is also suitable for monitoring diffuse contamination based on the statistical distribution of repeat datasets at the continental scale in a cost-effective manner.

Atmospheric CO2 Observations Reveal Strong Correlation Between Regional Net Biospheric Carbon Uptake and Solar-Induced Chlorophyll Fluorescence

NASA Astrophysics Data System (ADS)

Shiga, Yoichi P.; Tadić, Jovan M.; Qiu, Xuemei; Yadav, Vineet; Andrews, Arlyn E.; Berry, Joseph A.; Michalak, Anna M.

2018-01-01

Recent studies have shown the promise of remotely sensed solar-induced chlorophyll fluorescence (SIF) in informing terrestrial carbon exchange, but analyses have been limited to either plot level ( 1 km2) or hemispheric/global ( 108 km2) scales due to the lack of a direct measure of carbon exchange at intermediate scales. Here we use a network of atmospheric CO2 observations over North America to explore the value of SIF for informing net ecosystem exchange (NEE) at regional scales. We find that SIF explains space-time NEE patterns at regional ( 100 km2) scales better than a variety of other vegetation and climate indicators. We further show that incorporating SIF into an atmospheric inversion leads to a spatial redistribution of NEE estimates over North America, with more uptake attributed to agricultural regions and less to needleleaf forests. Our results highlight the synergy of ground-based and spaceborne carbon cycle observations.

INTEGRATING FIELD-BASED SAMPLING AND LANDSCAPE DATA FOR REGIONAL SCALE ASSESSMENTS: EXAMPLES FROM THE UNITED STATES MID-ATLANTIC REGION

EPA Science Inventory

Spatially explicit identification of status and changes in ecological conditions over large, regional areas is key to targeting and prioritizing areas for potential further study and environmental protection and restoration. A critical limitation to this point has been our abili...

Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

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

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.

Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

DOE PAGES

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; ...

2018-02-09

Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

What spatial scales are believable for climate model projections of sea surface temperature?

NASA Astrophysics Data System (ADS)

Kwiatkowski, Lester; Halloran, Paul R.; Mumby, Peter J.; Stephenson, David B.

2014-09-01

Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (<8°). Our findings suggest that output from current generation ESMs is not yet suitable for making sub-regional projections of change in coral bleaching frequency and other marine processes linked to SST warming.

Serial grouping of 2D-image regions with object-based attention in humans.

PubMed

Jeurissen, Danique; Self, Matthew W; Roelfsema, Pieter R

2016-06-13

After an initial stage of local analysis within the retina and early visual pathways, the human visual system creates a structured representation of the visual scene by co-selecting image elements that are part of behaviorally relevant objects. The mechanisms underlying this perceptual organization process are only partially understood. We here investigate the time-course of perceptual grouping of two-dimensional image-regions by measuring the reaction times of human participants and report that it is associated with the gradual spread of object-based attention. Attention spreads fastest over large and homogeneous areas and is slowed down at locations that require small-scale processing. We find that the time-course of the object-based selection process is well explained by a 'growth-cone' model, which selects surface elements in an incremental, scale-dependent manner. We discuss how the visual cortical hierarchy can implement this scale-dependent spread of object-based attention, leveraging the different receptive field sizes in distinct cortical areas.

MULTI-SCALE CONTROLS ON AND CONSEQUENCES OF AEOLIAN PROCESSES IN LANDSCAPE CHANGE IN ARID AND SEMI-ARID ENVIRONMENTS

EPA Science Inventory

This paper reviews the controls on aeolian processes and their consequences at plant-interspace, patch-landscape, and regional-global scales. Based on this review, we define the requirements for a cross-scale model of wind erosion in structurally complex arid and semiarid ecosyst...

Scaling up functional traits for ecosystem services with remote sensing: concepts and methods.

PubMed

Abelleira Martínez, Oscar J; Fremier, Alexander K; Günter, Sven; Ramos Bendaña, Zayra; Vierling, Lee; Galbraith, Sara M; Bosque-Pérez, Nilsa A; Ordoñez, Jenny C

2016-07-01

Ecosystem service-based management requires an accurate understanding of how human modification influences ecosystem processes and these relationships are most accurate when based on functional traits. Although trait variation is typically sampled at local scales, remote sensing methods can facilitate scaling up trait variation to regional scales needed for ecosystem service management. We review concepts and methods for scaling up plant and animal functional traits from local to regional spatial scales with the goal of assessing impacts of human modification on ecosystem processes and services. We focus our objectives on considerations and approaches for (1) conducting local plot-level sampling of trait variation and (2) scaling up trait variation to regional spatial scales using remotely sensed data. We show that sampling methods for scaling up traits need to account for the modification of trait variation due to land cover change and species introductions. Sampling intraspecific variation, stratification by land cover type or landscape context, or inference of traits from published sources may be necessary depending on the traits of interest. Passive and active remote sensing are useful for mapping plant phenological, chemical, and structural traits. Combining these methods can significantly improve their capacity for mapping plant trait variation. These methods can also be used to map landscape and vegetation structure in order to infer animal trait variation. Due to high context dependency, relationships between trait variation and remotely sensed data are not directly transferable across regions. We end our review with a brief synthesis of issues to consider and outlook for the development of these approaches. Research that relates typical functional trait metrics, such as the community-weighted mean, with remote sensing data and that relates variation in traits that cannot be remotely sensed to other proxies is needed. Our review narrows the gap between functional trait and remote sensing methods for ecosystem service management.

The Neutral Islands during the Late Epoch of Reionization

NASA Astrophysics Data System (ADS)

Xu, Yidong; Yue, Bin; Chen, Xuelei

2018-05-01

The large-scale structure of the ionization field during the epoch of reionization (EoR) can be modeled by the excursion set theory. While the growth of ionized regions during the early stage are described by the ``bubble model'', the shrinking process of neutral regions after the percolation of the ionized region calls for an ``island model''. An excursion set based analytical model and a semi-numerical code (islandFAST) have been developed. The ionizing background and the bubbles inside the islands are also included in the treatment. With two kinds of absorbers of ionizing photons, i.e. the large-scale under-dense neutral islands and the small-scale over-dense clumps, the ionizing background are self-consistently evolved in the model.

Segmentation of the Speaker's Face Region with Audiovisual Correlation

NASA Astrophysics Data System (ADS)

Liu, Yuyu; Sato, Yoichi

The ability to find the speaker's face region in a video is useful for various applications. In this work, we develop a novel technique to find this region within different time windows, which is robust against the changes of view, scale, and background. The main thrust of our technique is to integrate audiovisual correlation analysis into a video segmentation framework. We analyze the audiovisual correlation locally by computing quadratic mutual information between our audiovisual features. The computation of quadratic mutual information is based on the probability density functions estimated by kernel density estimation with adaptive kernel bandwidth. The results of this audiovisual correlation analysis are incorporated into graph cut-based video segmentation to resolve a globally optimum extraction of the speaker's face region. The setting of any heuristic threshold in this segmentation is avoided by learning the correlation distributions of speaker and background by expectation maximization. Experimental results demonstrate that our method can detect the speaker's face region accurately and robustly for different views, scales, and backgrounds.

Regional Climate Sensitivity- and Historical-Based Projections to 2100

NASA Astrophysics Data System (ADS)

Hébert, Raphaël.; Lovejoy, Shaun

2018-05-01

Reliable climate projections at the regional scale are needed in order to evaluate climate change impacts and inform policy. We develop an alternative method for projections based on the transient climate sensitivity (TCS), which relies on a linear relationship between the forced temperature response and the strongly increasing anthropogenic forcing. The TCS is evaluated at the regional scale (5° by 5°), and projections are made accordingly to 2100 using the high and low Representative Concentration Pathways emission scenarios. We find that there are large spatial discrepancies between the regional TCS from 5 historical data sets and 32 global climate model (GCM) historical runs and furthermore that the global mean GCM TCS is about 15% too high. Given that the GCM Representative Concentration Pathway scenario runs are mostly linear with respect to their (inadequate) TCS, we conclude that historical methods of regional projection are better suited given that they are directly calibrated on the real world (historical) climate.

Classification as a generic tool for characterising status and changes of regional scale groundwater systems

NASA Astrophysics Data System (ADS)

Barthel, Roland; Haaf, Ezra

2016-04-01

Regional hydrogeology is becoming increasingly important, but at the same time, scientifically sound, universal solutions for typical groundwater problems encountered on the regional scale are hard to find. While managers, decision-makers and state agencies operating on regional and national levels have always shown a strong interest in regional scale hydrogeology, researchers from academia tend to avoid the subject, focusing instead on local scales. Additionally, hydrogeology has always had a tendency to regard every problem as unique to its own site- and problem-specific context. Regional scale hydrogeology is therefore pragmatic rather than aiming at developing generic methodology (Barthel, 2014; Barthel and Banzhaf, 2016). One of the main challenges encountered on the regional scale in hydrogeology is the extreme heterogeneity that generally increases with the size of the studied area - paired with relative data scarcity. Even in well-monitored regions of the world, groundwater observations are usually clustered, leaving large areas without any direct data. However, there are many good reasons for assessing the status and predicting the behavior of groundwater systems under conditions of global change even for those areas and aquifers without observations. This is typically done by using rather coarsely discretized and / or poorly parameterized numerical models, or by using very simplistic conceptual hydrological models that do not take into account the complex three-dimensional geological setup. Numerical models heavily rely on local data and are resource-demanding. Conceptual hydrological models only deliver reliable information on groundwater if the geology is extremely simple. In this contribution, we present an approach to derive statistically relevant information for un-monitored areas, making use of existing information from similar localities that are or have been monitored. The approach combines site-specific knowledge with conceptual assumptions on the behavior of groundwater systems. It is based on the hypothesis that similar groundwater systems respond similarly to similar impacts. At its core is the classification of (i) static hydrogeological characteristics (such as aquifer geometry and hydraulic properties), (ii) dynamic changes of the boundary conditions (such as recharge, water levels in surface waters), and (iii) dynamic groundwater system responses (groundwater head and chemical parameters). The dependencies of system responses on explanatory variables are used to map knowledge from observed locations to areas without measurements. Classification of static and dynamic system features combined with information about known system properties and their dependencies provide insight into system behavior that cannot be directly derived through the analysis of raw data. Classification and dependency analysis could finally lead to a new framework for groundwater system assessment on the regional scale as a replacement or supplement to numerical groundwater models and catchment scale hydrological models. This contribution focusses on the main hydrogeological concepts underlying the approach while another EGU contribution (Haaf and Barthel, 2016) explains the methodologies used to classify groundwater systems. References: Barthel, R., 2014. A call for more fundamental science in regional hydrogeology. Hydrogeol J, 22(3): 507-510. Barthel, R., Banzhaf, S., 2016. Groundwater and Surface Water Interaction at the Regional-scale - A Review with Focus on Regional Integrated Models. Water Resour Manag, 30(1): 1-32. Haaf, E., Barthel, R., 2016. An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs. Abstract submitted to EGU General Assembly 2016, Vienna, Austria.

Regionalization of subsurface stormflow parameters of hydrologic models: Up-scaling from physically based numerical simulations at hillslope scale

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

Ali, Melkamu; Ye, Sheng; Li, Hongyi

2014-07-19

Subsurface stormflow is an important component of the rainfall-runoff response, especially in steep forested regions. However; its contribution is poorly represented in current generation of land surface hydrological models (LSMs) and catchment-scale rainfall-runoff models. The lack of physical basis of common parameterizations precludes a priori estimation (i.e. without calibration), which is a major drawback for prediction in ungauged basins, or for use in global models. This paper is aimed at deriving physically based parameterizations of the storage-discharge relationship relating to subsurface flow. These parameterizations are derived through a two-step up-scaling procedure: firstly, through simulations with a physically based (Darcian) subsurfacemore » flow model for idealized three dimensional rectangular hillslopes, accounting for within-hillslope random heterogeneity of soil hydraulic properties, and secondly, through subsequent up-scaling to the catchment scale by accounting for between-hillslope and within-catchment heterogeneity of topographic features (e.g., slope). These theoretical simulation results produced parameterizations of the storage-discharge relationship in terms of soil hydraulic properties, topographic slope and their heterogeneities, which were consistent with results of previous studies. Yet, regionalization of the resulting storage-discharge relations across 50 actual catchments in eastern United States, and a comparison of the regionalized results with equivalent empirical results obtained on the basis of analysis of observed streamflow recession curves, revealed a systematic inconsistency. It was found that the difference between the theoretical and empirically derived results could be explained, to first order, by climate in the form of climatic aridity index. This suggests a possible codependence of climate, soils, vegetation and topographic properties, and suggests that subsurface flow parameterization needed for ungauged locations must account for both the physics of flow in heterogeneous landscapes, and the co-dependence of soil and topographic properties with climate, including possibly the mediating role of vegetation.« less

Impact of livestock Scale on Rice Production in Battambang of Cambodia

NASA Astrophysics Data System (ADS)

Siek, D.; Xu, S. W.; Wyu; Ahmed, A.-G.

2017-10-01

Increasing the awareness of environmental protection especially in the rural regions is important as most the farmers reside in that region. Crop-livestock proudciton has proven in many ways to encourage environmental protection. This study analyzes among other factors the impacto of livestock scale on rice production. Two regressions: Ordinary Least Square (OLS) and stepwise regression was applied to investigate these interrelationship. The result stress of three factors encouraging livestock production namely size of farmland, scale of livestock and income acquired from other jobs. The study further provides recommends to the government based on the findings of the study.

Pore-scale simulations of concentration tails in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Di Palma, Paolo Roberto; Parmigiani, Andrea; Huber, Christian; Guyennon, Nicolas; Viotti, Paolo

2017-10-01

The retention of contaminants in the finest and less-conductive regions of natural aquifer is known to strongly affect the decontamination of polluted aquifers. In fact, contaminant transfer from low to high mobility regions at the back end of a contaminant plume (i.e. back diffusion) is responsible for the long-term release of contaminants during remediation operation. In this paper, we perform pore-scale calculations for the transport of contaminant through heterogeneous porous media composed of low and high mobility regions with two objectives: (i) study the effect of permeability contrast and solute transport conditions on the exchange of solutes between mobile and immobile regions and (ii) estimate the mass of contaminants sequestered in low mobility regions based on concentration breakthrough curves.

An individual-based model of skipjack tuna (Katsuwonus pelamis) movement in the tropical Pacific ocean

NASA Astrophysics Data System (ADS)

Scutt Phillips, Joe; Sen Gupta, Alex; Senina, Inna; van Sebille, Erik; Lange, Michael; Lehodey, Patrick; Hampton, John; Nicol, Simon

2018-05-01

The distribution of marine species is often modeled using Eulerian approaches, in which changes to population density or abundance are calculated at fixed locations in space. Conversely, Lagrangian, or individual-based, models simulate the movement of individual particles moving in continuous space, with broader-scale patterns such as distribution being an emergent property of many, potentially adaptive, individuals. These models offer advantages in examining dynamics across spatiotemporal scales and making comparisons with observations from individual-scale data. Here, we introduce and describe such a model, the Individual-based Kinesis, Advection and Movement of Ocean ANimAls model (Ikamoana), which we use to replicate the movement processes of an existing Eulerian model for marine predators (the Spatial Ecosystem and Population Dynamics Model, SEAPODYM). Ikamoana simulates the movement of either individual or groups of animals by physical ocean currents, habitat-dependent stochastic movements (kinesis), and taxis movements representing active searching behaviours. Applying our model to Pacific skipjack tuna (Katsuwonus pelamis), we show that it accurately replicates the evolution of density distribution simulated by SEAPODYM with low time-mean error and a spatial correlation of density that exceeds 0.96 at all times. We demonstrate how the Lagrangian approach permits easy tracking of individuals' trajectories for examining connectivity between different regions, and show how the model can provide independent estimates of transfer rates between commonly used assessment regions. In particular, we find that retention rates in most assessment regions are considerably smaller (up to a factor of 2) than those estimated by this population of skipjack's primary assessment model. Moreover, these rates are sensitive to ocean state (e.g. El Nino vs La Nina) and so assuming fixed transfer rates between regions may lead to spurious stock estimates. A novel feature of the Lagrangian approach is that individual schools can be tracked through time, and we demonstrate that movement between two assessment regions at broad temporal scales includes extended transits through other regions at finer-scales. Finally, we discuss the utility of this modeling framework for the management of marine reserves, designing effective monitoring programmes, and exploring hypotheses regarding the behaviour of hard-to-observe oceanic animals.

Analysis of the Nonlinear Trends and Non-Stationary Oscillations of Regional Precipitation in Xinjiang, Northwestern China, Using Ensemble Empirical Mode Decomposition

PubMed Central

Guo, Bin; Chen, Zhongsheng; Guo, Jinyun; Liu, Feng; Chen, Chuanfa; Liu, Kangli

2016-01-01

Changes in precipitation could have crucial influences on the regional water resources in arid regions such as Xinjiang. It is necessary to understand the intrinsic multi-scale variations of precipitation in different parts of Xinjiang in the context of climate change. In this study, based on precipitation data from 53 meteorological stations in Xinjiang during 1960–2012, we investigated the intrinsic multi-scale characteristics of precipitation variability using an adaptive method named ensemble empirical mode decomposition (EEMD). Obvious non-linear upward trends in precipitation were found in the north, south, east and the entire Xinjiang. Changes in precipitation in Xinjiang exhibited significant inter-annual scale (quasi-2 and quasi-6 years) and inter-decadal scale (quasi-12 and quasi-23 years). Moreover, the 2–3-year quasi-periodic fluctuation was dominant in regional precipitation and the inter-annual variation had a considerable effect on the regional-scale precipitation variation in Xinjiang. We also found that there were distinctive spatial differences in variation trends and turning points of precipitation in Xinjiang. The results of this study indicated that compared to traditional decomposition methods, the EEMD method, without using any a priori determined basis functions, could effectively extract the reliable multi-scale fluctuations and reveal the intrinsic oscillation properties of climate elements. PMID:27007388

51. Roof plans, General Services Administration, Construction Management Division, Region ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

51. Roof plans, General Services Administration, Construction Management Division, Region 2, New York, October 29, 1976. Scale 1/31=1. - U.S. Navy Fleet Supply Base, Storehouse No. 1, 830 Third Avenue, Brooklyn, Kings County, NY

Suitability of temperature sum models to simulate the flowering period of birches on regional scale as basis for realistic predictions of the allergenic potential of atmospheric pollen loads

NASA Astrophysics Data System (ADS)

Biernath, Christian; Hauck, Julia; Klein, Christian; Thieme, Christoph; Heinlein, Florian; Priesack, Eckart

2014-05-01

Persons susceptible to allergenic pollen grains need to apply suppressive pharmacy before the occurrence of the first allergy symptoms. Patient targeted medication could be improved if forecasts of the allergenic potential of pollen (biochemical composition of the pollen grain) and the onset, duration, and end of the pollen season are precise on regional scale. In plant tissue the biochemical composition may change within hours due to the resource availability for plant growth and plant internal nutrient re-mobilization. As these processes highly depend on both, the environmental conditions and the development stage of a plant, precise simulations of the onset and duration of the flowering period are crucial to determine the allergenic potential of tissues and pollen. Here, dynamic plant models that consider the dependence of the chemical composition of tissue on the development stage of the plant embedded in process-based ecosystem models seem promising tools; however, today dynamic plant growth is widely ignored in simulations of atmospheric pollen loads. In this study we raise the question whether frequently applied temperature sum models (TSM) could precisely simulate the plant development stages in case of birches on regional scale. These TSM integrate average temperatures above a base temperature below which no further plant development is assumed. In this study, we therefore tested the ability of TSM to simulate the flowering period of birches on more than 100 sites in Bavaria, Germany over a period of three years (2010-2012). Our simulations indicate that the often applied base temperatures between 2.3°C and 3.5°C for the integration of daily or hourly average temperatures, respectively, in Europe are too high to adequately simulate the onset of birch flowering in Bavaria where a base temperature of 1°C seems more convenient. A more regional calibration of the models to sub-regions in Bavaria with comparable climatic conditions could further improve the simulation results if compared to simulations using a model that was adjusted to only one representative location in Bavaria. Our simulation results suggest that birch phenology needs to be modelled on a more regional scale to derive precise predictions of the flowering period. Some weak simulation results are suspected to be due to the high genetic diversity of birches and their high adaptive potential to a wide range of environmental conditions which indeed is a characteristic for many pioneer species. The high adaptive potential could be an explanation why authors who calibrate their models to other climatic regions observe better simulation results using higher base temperatures. However, our simulations indicate that the simulation results may be biased if the base temperatures are assumed constant for one species and transferred to larger or smaller scales, to other regions with different climatic conditions, or when applied to extrapolate birch pollen seasons to future climate conditions.

A Parallel Sliding Region Algorithm to Make Agent-Based Modeling Possible for a Large-Scale Simulation: Modeling Hepatitis C Epidemics in Canada.

PubMed

Wong, William W L; Feng, Zeny Z; Thein, Hla-Hla

2016-11-01

Agent-based models (ABMs) are computer simulation models that define interactions among agents and simulate emergent behaviors that arise from the ensemble of local decisions. ABMs have been increasingly used to examine trends in infectious disease epidemiology. However, the main limitation of ABMs is the high computational cost for a large-scale simulation. To improve the computational efficiency for large-scale ABM simulations, we built a parallelizable sliding region algorithm (SRA) for ABM and compared it to a nonparallelizable ABM. We developed a complex agent network and performed two simulations to model hepatitis C epidemics based on the real demographic data from Saskatchewan, Canada. The first simulation used the SRA that processed on each postal code subregion subsequently. The second simulation processed the entire population simultaneously. It was concluded that the parallelizable SRA showed computational time saving with comparable results in a province-wide simulation. Using the same method, SRA can be generalized for performing a country-wide simulation. Thus, this parallel algorithm enables the possibility of using ABM for large-scale simulation with limited computational resources.

Fast hierarchical knowledge-based approach for human face detection in color images

NASA Astrophysics Data System (ADS)

Jiang, Jun; Gong, Jie; Zhang, Guilin; Hu, Ruolan

2001-09-01

This paper presents a fast hierarchical knowledge-based approach for automatically detecting multi-scale upright faces in still color images. The approach consists of three levels. At the highest level, skin-like regions are determinated by skin model, which is based on the color attributes hue and saturation in HSV color space, as well color attributes red and green in normalized color space. In level 2, a new eye model is devised to select human face candidates in segmented skin-like regions. An important feature of the eye model is that it is independent of the scale of human face. So it is possible for finding human faces in different scale with scanning image only once, and it leads to reduction the computation time of face detection greatly. In level 3, a human face mosaic image model, which is consistent with physical structure features of human face well, is applied to judge whether there are face detects in human face candidate regions. This model includes edge and gray rules. Experiment results show that the approach has high robustness and fast speed. It has wide application perspective at human-computer interactions and visual telephone etc.

An analysis of the impacts of global climate and emissions changes on regional tropospheric ozone

NASA Technical Reports Server (NTRS)

John, Kuruvilla; Crist, Kevin C.; Carmichael, Gregory R.

1994-01-01

Many of the synergistic impacts resulting from future changes in emissions as well as changes in ambient temperature, moisture, and UV flux have not been quantified. A three-dimensional regional-scale photo-chemical model (STEM-2) is used in this study to evaluate these perturbations to trace gas cycles over the eastern half of the United States of America. The model was successfully used to simulate a regional-scale ozone episode (base case - June 1984) and four perturbations scenarios - viz., perturbed emissions, temperature, water vapor column, and incoming UV flux cases, and a future scenario (for the year 2034). The impact of these perturbation scenarios on the distribution of ozone and other major pollutants such as SO2 and sulfates were analyzed in detail. The spatial distribution and the concentration of ozone at the surface increased by about 5-15 percent for most cases except for the perturbed water vapor case. The regional scale surface ozone concentration distribution for the year 2034 (future scenario) showed an increase of non-attainment areas. The rural areas of Pennsylvania, West Virginia, and Georgia showed the largest change in the surface ozone field for the futuristic scenario when compared to the base case.

Air-quality in the mid-21st century for the city of Paris under two climate scenarios; from regional to local scale

NASA Astrophysics Data System (ADS)

Markakis, K.; Valari, M.; Colette, A.; Sanchez, O.; Perrussel, O.; Honore, C.; Vautard, R.; Klimont, Z.; Rao, S.

2014-01-01

Ozone and PM2.5 concentrations over the city of Paris are modeled with the CHIMERE air-quality model at 4 km × 4 km horizontal resolution for two future emission scenarios. High-resolution (1 km × 1 km) emission projection until 2020 for the greater Paris region is developed by local experts (AIRPARIF) and is further extended to year 2050 based on regional scale emission projections developed by the Global Energy Assessment. Model evaluation is performed based on a 10 yr control simulation. Ozone is in very good agreement with measurements while PM2.5 is underestimated by 20% over the urban area mainly due to a large wet bias in wintertime precipitation. A significant increase of maximum ozone relative to present time levels over Paris is modeled under the "business as usual" scenario (+7 ppb) while a more optimistic mitigation scenario leads to moderate ozone decrease (-3.5 ppb) in year 2050. These results are substantially different to previous regional scale projections where 2050 ozone is found to decrease under both future scenarios. A sensitivity analysis showed that this difference is due to the fact that ozone formation over Paris at the current, urban scale study, is driven by VOC-limited chemistry, whereas at the regional scale ozone formation occurs under NOx-sensitive conditions. This explains why the sharp NOx reductions implemented in the future scenarios have a different effect on ozone projections at different scales. In rural areas projections at both scales yield similar results showing that the longer time-scale processes of emission transport and ozone formation are less sensitive to model resolution. PM2.5 concentrations decrease by 78% and 89% under "business as usual" and "mitigation" scenarios respectively compared to present time period. The reduction is much more prominent over the urban part of the domain due to the effective reductions of road transport and residential emissions resulting in the smoothing of the large urban increment modelled in the control simulation.

An innovative expression model of human health risk based on the quantitative analysis of soil metals sources contribution in different spatial scales.

PubMed

Zhang, Yimei; Li, Shuai; Wang, Fei; Chen, Zhuang; Chen, Jie; Wang, Liqun

2018-09-01

Toxicity of heavy metals from industrialization poses critical concern, and analysis of sources associated with potential human health risks is of unique significance. Assessing human health risk of pollution sources (factored health risk) concurrently in the whole and the sub region can provide more instructive information to protect specific potential victims. In this research, we establish a new expression model of human health risk based on quantitative analysis of sources contribution in different spatial scales. The larger scale grids and their spatial codes are used to initially identify the level of pollution risk, the type of pollution source and the sensitive population at high risk. The smaller scale grids and their spatial codes are used to identify the contribution of various sources of pollution to each sub region (larger grid) and to assess the health risks posed by each source for each sub region. The results of case study show that, for children (sensitive populations, taking school and residential area as major region of activity), the major pollution source is from the abandoned lead-acid battery plant (ALP), traffic emission and agricultural activity. The new models and results of this research present effective spatial information and useful model for quantifying the hazards of source categories and human health a t complex industrial system in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

A large-scale initiative to disseminate an evidence-based drug abuse prevention program in Italy: Lessons learned for practitioners and researchers.

PubMed

Velasco, Veronica; Griffin, Kenneth W; Antichi, Mariella; Celata, Corrado

2015-10-01

Across developed countries, experimentation with alcohol, tobacco, and other drugs often begins in the early adolescent years. Several evidence-based programs have been developed to prevent adolescent substance use. Many of the most rigorously tested and empirically supported prevention programs were initially developed and tested in the United States. Increasingly, these interventions are being adopted for use in Europe and throughout the world. This paper reports on a large-scale comprehensive initiative designed to select, adapt, implement, and sustain an evidence-based drug abuse prevention program in Italy. As part of a large-scale regionally funded collaboration in the Lombardy region of Italy, we report on processes through which a team of stakeholders selected, translated and culturally adapted, planned, implemented and evaluated the Life Skills Training (LST) school-based drug abuse prevention program, an evidence-based intervention developed in the United States. We discuss several challenges and lessons learned and implications for prevention practitioners and researchers attempting to undertake similar international dissemination projects. We review several published conceptual models designed to promote the replication and widespread dissemination of effective programs, and discuss their strengths and limitations in the context of planning and implementing a complex, large-scale real-world dissemination effort. Copyright © 2015 Elsevier Ltd. All rights reserved.

Application and comparison of the SCS-CN-based rainfall-runoff model in meso-scale watershed and field scale

NASA Astrophysics Data System (ADS)

Luo, L.; Wang, Z.

2010-12-01

Soil Conservation Service Curve Number (SCS-CN) based hydrologic model, has widely been used for agricultural watersheds in recent years. However, there will be relative error when applying it due to differentiation of geographical and climatological conditions. This paper introduces a more adaptable and propagable model based on the modified SCS-CN method, which specializes into two different scale cases of research regions. Combining the typical conditions of the Zhanghe irrigation district in southern part of China, such as hydrometeorologic conditions and surface conditions, SCS-CN based models were established. The Xinbu-Qiao River basin (area =1207 km2) and the Tuanlin runoff test area (area =2.87 km2)were taken as the study areas of basin scale and field scale in Zhanghe irrigation district. Applications were extended from ordinary meso-scale watershed to field scale in Zhanghe paddy field-dominated irrigated . Based on actual measurement data of land use, soil classification, hydrology and meteorology, quantitative evaluation and modifications for two coefficients, i.e. preceding loss and runoff curve, were proposed with corresponding models, table of CN values for different landuse and AMC(antecedent moisture condition) grading standard fitting for research cases were proposed. The simulation precision was increased by putting forward a 12h unit hydrograph of the field area, and 12h unit hydrograph were simplified. Comparison between different scales show that it’s more effectively to use SCS-CN model on field scale after parameters calibrated in basin scale These results can help discovering the rainfall-runoff rule in the district. Differences of established SCS-CN model's parameters between the two study regions are also considered. Varied forms of landuse and impacts of human activities were the important factors which can impact the rainfall-runoff relations in Zhanghe irrigation district.

Relationships between aquatic vegetation and water turbidity: A field survey across seasons and spatial scales

PubMed Central

Austin, Åsa N.; Hansen, Joakim P.; Donadi, Serena; Eklöf, Johan S.

2017-01-01

Field surveys often show that high water turbidity limits cover of aquatic vegetation, while many small-scale experiments show that vegetation can reduce turbidity by decreasing water flow, stabilizing sediments, and competing with phytoplankton for nutrients. Here we bridged these two views by exploring the direction and strength of causal relationships between aquatic vegetation and turbidity across seasons (spring and late summer) and spatial scales (local and regional), using causal modeling based on data from a field survey along the central Swedish Baltic Sea coast. The two best-fitting regional-scale models both suggested that in spring, high cover of vegetation reduces water turbidity. In summer, the relationships differed between the two models; in the first model high vegetation cover reduced turbidity; while in the second model reduction of summer turbidity by high vegetation cover in spring had a positive effect on summer vegetation which suggests a positive feedback of vegetation on itself. Nitrogen load had a positive effect on turbidity in both seasons, which was comparable in strength to the effect of vegetation on turbidity. To assess whether the effect of vegetation was primarily caused by sediment stabilization or a reduction of phytoplankton, we also tested models where turbidity was replaced by phytoplankton fluorescence or sediment-driven turbidity. The best-fitting regional-scale models suggested that high sediment-driven turbidity in spring reduces vegetation cover in summer, which in turn has a negative effect on sediment-driven turbidity in summer, indicating a potential positive feedback of sediment-driven turbidity on itself. Using data at the local scale, few relationships were significant, likely due to the influence of unmeasured variables and/or spatial heterogeneity. In summary, causal modeling based on data from a large-scale field survey suggested that aquatic vegetation can reduce turbidity at regional scales, and that high vegetation cover vs. high sediment-driven turbidity may represent two self-enhancing, alternative states of shallow bay ecosystems. PMID:28854185

Relationships between aquatic vegetation and water turbidity: A field survey across seasons and spatial scales.

PubMed

Austin, Åsa N; Hansen, Joakim P; Donadi, Serena; Eklöf, Johan S

2017-01-01

Field surveys often show that high water turbidity limits cover of aquatic vegetation, while many small-scale experiments show that vegetation can reduce turbidity by decreasing water flow, stabilizing sediments, and competing with phytoplankton for nutrients. Here we bridged these two views by exploring the direction and strength of causal relationships between aquatic vegetation and turbidity across seasons (spring and late summer) and spatial scales (local and regional), using causal modeling based on data from a field survey along the central Swedish Baltic Sea coast. The two best-fitting regional-scale models both suggested that in spring, high cover of vegetation reduces water turbidity. In summer, the relationships differed between the two models; in the first model high vegetation cover reduced turbidity; while in the second model reduction of summer turbidity by high vegetation cover in spring had a positive effect on summer vegetation which suggests a positive feedback of vegetation on itself. Nitrogen load had a positive effect on turbidity in both seasons, which was comparable in strength to the effect of vegetation on turbidity. To assess whether the effect of vegetation was primarily caused by sediment stabilization or a reduction of phytoplankton, we also tested models where turbidity was replaced by phytoplankton fluorescence or sediment-driven turbidity. The best-fitting regional-scale models suggested that high sediment-driven turbidity in spring reduces vegetation cover in summer, which in turn has a negative effect on sediment-driven turbidity in summer, indicating a potential positive feedback of sediment-driven turbidity on itself. Using data at the local scale, few relationships were significant, likely due to the influence of unmeasured variables and/or spatial heterogeneity. In summary, causal modeling based on data from a large-scale field survey suggested that aquatic vegetation can reduce turbidity at regional scales, and that high vegetation cover vs. high sediment-driven turbidity may represent two self-enhancing, alternative states of shallow bay ecosystems.

Behavior of predicted convective clouds and precipitation in the high-resolution Unified Model over the Indian summer monsoon region

NASA Astrophysics Data System (ADS)

Jayakumar, A.; Sethunadh, Jisesh; Rakhi, R.; Arulalan, T.; Mohandas, Saji; Iyengar, Gopal R.; Rajagopal, E. N.

2017-05-01

National Centre for Medium Range Weather Forecasting high-resolution regional convective-scale Unified Model with latest tropical science settings is used to evaluate vertical structure of cloud and precipitation over two prominent monsoon regions: Western Ghats (WG) and Monsoon Core Zone (MCZ). Model radar reflectivity generated using Cloud Feedback Model Intercomparison Project Observation Simulator Package along with CloudSat profiling radar reflectivity is sampled for an active synoptic situation based on a new method using Budyko's index of turbulence (BT). Regime classification based on BT-precipitation relationship is more predominant during the active monsoon period when convective-scale model's resolution increases from 4 km to 1.5 km. Model predicted precipitation and vertical distribution of hydrometeors are found to be generally in agreement with Global Precipitation Measurement products and BT-based CloudSat observation, respectively. Frequency of occurrence of radar reflectivity from model implies that the low-level clouds below freezing level is underestimated compared to the observations over both regions. In addition, high-level clouds in the model predictions are much lesser over WG than MCZ.

Exploring reanalysis application for the purposes of climatological applications at regional scale

NASA Astrophysics Data System (ADS)

Kaspar, F.; Kaiser-Weiss, A.; Obregon, A.; Borsche, M.

2014-12-01

Recent advances in reanalysis methods yield new tools for climatological application. Here we use applications in Germany to discuss methodological issues at regional scale. Especially in the field of renewable energy planning and production there is a need for climatological information across all spatial scales, i.e., from climatology at a certain site to the spatial scale of national renewable energy production. Also, there is the need for the temporal resolution between the scales of a few minutes up to decadal changes. We explore the spatio-temporal scales where reanalyses can be used with benefit together with the traditional approaches which are based on station measurements only. Reanalyses can provide valuable additional information on larger scale variability, e.g. multi-annual variation over Germany. However, the change in the observing system, model errors and biases have to be carefully considered. On the other hand, the ground-based observation networks suffer from change of the station distribution, changes in instrumentation, measurements procedures and quality control as well as local changes which might modify their spatial representativity. All these effects might often been unknown or hard to characterize, although plenty of the meta-data information has been recorded for the German stations. European research activities on global and regional reanalysis are supported by the Framework Program 7 (FP7) of the European Commission as a preparation activity for the European COPERNICUS climate change service. Here we start from the user requirements for reanalyses as they were collected in the FP7 project CORE-CLIMAX. Second, we give an overview over the methods to determine whether a specific reanalysis is fit for a certain purpose (discussed in FP7 projects CORE-CLIMAX and UERRA) . Thirdly, we compare for an example application the feedback statistics from global (ERA-Interim) and regional (HErZ - COSMO) reanalyses and show which conclusion can be drawn. Finally, the wind climatologies derived from the different reanalyses (ERA-Interim, ERA-20C, HErZ-COSMO) are compared with point measurements and gridded field climatologies derived from ground-based stations, illustrating the added value of the reanalysis fields.

Regionalization of meso-scale physically based nitrogen modeling outputs to the macro-scale by the use of regression trees

NASA Astrophysics Data System (ADS)

Künne, A.; Fink, M.; Kipka, H.; Krause, P.; Flügel, W.-A.

2012-06-01

In this paper, a method is presented to estimate excess nitrogen on large scales considering single field processes. The approach was implemented by using the physically based model J2000-S to simulate the nitrogen balance as well as the hydrological dynamics within meso-scale test catchments. The model input data, the parameterization, the results and a detailed system understanding were used to generate the regression tree models with GUIDE (Loh, 2002). For each landscape type in the federal state of Thuringia a regression tree was calibrated and validated using the model data and results of excess nitrogen from the test catchments. Hydrological parameters such as precipitation and evapotranspiration were also used to predict excess nitrogen by the regression tree model. Hence they had to be calculated and regionalized as well for the state of Thuringia. Here the model J2000g was used to simulate the water balance on the macro scale. With the regression trees the excess nitrogen was regionalized for each landscape type of Thuringia. The approach allows calculating the potential nitrogen input into the streams of the drainage area. The results show that the applied methodology was able to transfer the detailed model results of the meso-scale catchments to the entire state of Thuringia by low computing time without losing the detailed knowledge from the nitrogen transport modeling. This was validated with modeling results from Fink (2004) in a catchment lying in the regionalization area. The regionalized and modeled excess nitrogen correspond with 94%. The study was conducted within the framework of a project in collaboration with the Thuringian Environmental Ministry, whose overall aim was to assess the effect of agro-environmental measures regarding load reduction in the water bodies of Thuringia to fulfill the requirements of the European Water Framework Directive (Bäse et al., 2007; Fink, 2006; Fink et al., 2007).

Cities and regions in Britain through hierarchical percolation

NASA Astrophysics Data System (ADS)

Arcaute, Elsa; Molinero, Carlos; Hatna, Erez; Murcio, Roberto; Vargas-Ruiz, Camilo; Masucci, A. Paolo; Batty, Michael

2016-04-01

Urban systems present hierarchical structures at many different scales. These are observed as administrative regional delimitations which are the outcome of complex geographical, political and historical processes which leave almost indelible footprints on infrastructure such as the street network. In this work, we uncover a set of hierarchies in Britain at different scales using percolation theory on the street network and on its intersections which are the primary points of interaction and urban agglomeration. At the larger scales, the observed hierarchical structures can be interpreted as regional fractures of Britain, observed in various forms, from natural boundaries, such as National Parks, to regional divisions based on social class and wealth such as the well-known North-South divide. At smaller scales, cities are generated through recursive percolations on each of the emerging regional clusters. We examine the evolution of the morphology of the system as a whole, by measuring the fractal dimension of the clusters at each distance threshold in the percolation. We observe that this reaches a maximum plateau at a specific distance. The clusters defined at this distance threshold are in excellent correspondence with the boundaries of cities recovered from satellite images, and from previous methods using population density.

Multi-dimension and Comprehensive Assessment on the Utilizing and Sharing of Regional Large-Scale Scientific Equipment

PubMed Central

Li, Chen; Yongbo, Lv; Chi, Chen

2015-01-01

Based on the data from 30 provincial regions in China, an assessment and empirical analysis was carried out on the utilizing and sharing of the large-scale scientific equipment with a comprehensive assessment model established on the three dimensions, namely, equipment, utilization and sharing. The assessment results were interpreted in light of relevant policies. The results showed that on the whole, the overall development level in the provincial regions in eastern and central China is higher than that in western China. This is mostly because of the large gap among the different provincial regions with respect to the equipped level. But in terms of utilizing and sharing, some of the Western provincial regions, such as Ningxia, perform well, which is worthy of our attention. Policy adjustment targeting at the differentiation, elevation of the capacity of the equipment management personnel, perfection of the sharing and cooperation platform, and the promotion of the establishment of open sharing funds, are all important measures to promote the utilization and sharing of the large-scale scientific equipment and to narrow the gap among different regions. PMID:25937850

A regional-scale ecological risk framework for environmental flow evaluations

NASA Astrophysics Data System (ADS)

O'Brien, Gordon C.; Dickens, Chris; Hines, Eleanor; Wepener, Victor; Stassen, Retha; Quayle, Leo; Fouchy, Kelly; MacKenzie, James; Graham, P. Mark; Landis, Wayne G.

2018-02-01

Environmental flow (E-flow) frameworks advocate holistic, regional-scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in a socio-ecological context as best practice. Regional-scale ecological risk assessments of multiple stressors to social and ecological endpoints, which address ecosystem dynamism, have been undertaken internationally at different spatial scales using the relative-risk model since the mid-1990s. With the recent incorporation of Bayesian belief networks into the relative-risk model, a robust regional-scale ecological risk assessment approach is available that can contribute to achieving the best practice recommendations of E-flow frameworks. PROBFLO is a holistic E-flow assessment method that incorporates the relative-risk model and Bayesian belief networks (BN-RRM) into a transparent probabilistic modelling tool that addresses uncertainty explicitly. PROBFLO has been developed to evaluate the socio-ecological consequences of historical, current and future water resource use scenarios and generate E-flow requirements on regional spatial scales. The approach has been implemented in two regional-scale case studies in Africa where its flexibility and functionality has been demonstrated. In both case studies the evidence-based outcomes facilitated informed environmental management decision making, with trade-off considerations in the context of social and ecological aspirations. This paper presents the PROBFLO approach as applied to the Senqu River catchment in Lesotho and further developments and application in the Mara River catchment in Kenya and Tanzania. The 10 BN-RRM procedural steps incorporated in PROBFLO are demonstrated with examples from both case studies. PROBFLO can contribute to the adaptive management of water resources and contribute to the allocation of resources for sustainable use of resources and address protection requirements.

Probing Mantle Heterogeneity Across Spatial Scales

NASA Astrophysics Data System (ADS)

Hariharan, A.; Moulik, P.; Lekic, V.

2017-12-01

Inferences of mantle heterogeneity in terms of temperature, composition, grain size, melt and crystal structure may vary across local, regional and global scales. Probing these scale-dependent effects require quantitative comparisons and reconciliation of tomographic models that vary in their regional scope, parameterization, regularization and observational constraints. While a range of techniques like radial correlation functions and spherical harmonic analyses have revealed global features like the dominance of long-wavelength variations in mantle heterogeneity, they have limited applicability for specific regions of interest like subduction zones and continental cratons. Moreover, issues like discrepant 1-D reference Earth models and related baseline corrections have impeded the reconciliation of heterogeneity between various regional and global models. We implement a new wavelet-based approach that allows for structure to be filtered simultaneously in both the spectral and spatial domain, allowing us to characterize heterogeneity on a range of scales and in different geographical regions. Our algorithm extends a recent method that expanded lateral variations into the wavelet domain constructed on a cubed sphere. The isolation of reference velocities in the wavelet scaling function facilitates comparisons between models constructed with arbitrary 1-D reference Earth models. The wavelet transformation allows us to quantify the scale-dependent consistency between tomographic models in a region of interest and investigate the fits to data afforded by heterogeneity at various dominant wavelengths. We find substantial and spatially varying differences in the spectrum of heterogeneity between two representative global Vp models constructed using different data and methodologies. Applying the orthonormality of the wavelet expansion, we isolate detailed variations in velocity from models and evaluate additional fits to data afforded by adding such complexities to long-wavelength variations. Our method provides a way to probe and evaluate localized features in a multi-scale description of mantle heterogeneity.

High-resolution mapping of forest carbon stocks in the Colombian Amazon

NASA Astrophysics Data System (ADS)

Asner, G. P.; Clark, J. K.; Mascaro, J.; Galindo García, G. A.; Chadwick, K. D.; Navarrete Encinales, D. A.; Paez-Acosta, G.; Cabrera Montenegro, E.; Kennedy-Bowdoin, T.; Duque, Á.; Balaji, A.; von Hildebrand, P.; Maatoug, L.; Bernal, J. F. Phillips; Yepes Quintero, A. P.; Knapp, D. E.; García Dávila, M. C.; Jacobson, J.; Ordóñez, M. F.

2012-07-01

High-resolution mapping of tropical forest carbon stocks can assist forest management and improve implementation of large-scale carbon retention and enhancement programs. Previous high-resolution approaches have relied on field plot and/or light detection and ranging (LiDAR) samples of aboveground carbon density, which are typically upscaled to larger geographic areas using stratification maps. Such efforts often rely on detailed vegetation maps to stratify the region for sampling, but existing tropical forest maps are often too coarse and field plots too sparse for high-resolution carbon assessments. We developed a top-down approach for high-resolution carbon mapping in a 16.5 million ha region (> 40%) of the Colombian Amazon - a remote landscape seldom documented. We report on three advances for large-scale carbon mapping: (i) employing a universal approach to airborne LiDAR-calibration with limited field data; (ii) quantifying environmental controls over carbon densities; and (iii) developing stratification- and regression-based approaches for scaling up to regions outside of LiDAR coverage. We found that carbon stocks are predicted by a combination of satellite-derived elevation, fractional canopy cover and terrain ruggedness, allowing upscaling of the LiDAR samples to the full 16.5 million ha region. LiDAR-derived carbon maps have 14% uncertainty at 1 ha resolution, and the regional map based on stratification has 28% uncertainty in any given hectare. High-resolution approaches with quantifiable pixel-scale uncertainties will provide the most confidence for monitoring changes in tropical forest carbon stocks. Improved confidence will allow resource managers and decision makers to more rapidly and effectively implement actions that better conserve and utilize forests in tropical regions.

High-resolution Mapping of Forest Carbon Stocks in the Colombian Amazon

NASA Astrophysics Data System (ADS)

Asner, G. P.; Clark, J. K.; Mascaro, J.; Galindo García, G. A.; Chadwick, K. D.; Navarrete Encinales, D. A.; Paez-Acosta, G.; Cabrera Montenegro, E.; Kennedy-Bowdoin, T.; Duque, Á.; Balaji, A.; von Hildebrand, P.; Maatoug, L.; Bernal, J. F. Phillips; Knapp, D. E.; García Dávila, M. C.; Jacobson, J.; Ordóñez, M. F.

2012-03-01

High-resolution mapping of tropical forest carbon stocks can assist forest management and improve implementation of large-scale carbon retention and enhancement programs. Previous high-resolution approaches have relied on field plot and/or Light Detection and Ranging (LiDAR) samples of aboveground carbon density, which are typically upscaled to larger geographic areas using stratification maps. Such efforts often rely on detailed vegetation maps to stratify the region for sampling, but existing tropical forest maps are often too coarse and field plots too sparse for high resolution carbon assessments. We developed a top-down approach for high-resolution carbon mapping in a 16.5 million ha region (>40 %) of the Colombian Amazon - a remote landscape seldom documented. We report on three advances for large-scale carbon mapping: (i) employing a universal approach to airborne LiDAR-calibration with limited field data; (ii) quantifying environmental controls over carbon densities; and (iii) developing stratification- and regression-based approaches for scaling up to regions outside of LiDAR coverage. We found that carbon stocks are predicted by a combination of satellite-derived elevation, fractional canopy cover and terrain ruggedness, allowing upscaling of the LiDAR samples to the full 16.5 million ha region. LiDAR-derived carbon mapping samples had 14.6 % uncertainty at 1 ha resolution, and regional maps based on stratification and regression approaches had 25.6 % and 29.6 % uncertainty, respectively, in any given hectare. High-resolution approaches with reported local-scale uncertainties will provide the most confidence for monitoring changes in tropical forest carbon stocks. Improved confidence will allow resource managers and decision-makers to more rapidly and effectively implement actions that better conserve and utilize forests in tropical regions.

Analysis of Land-Use Effects on Landscape Patterns and Biological Diversity in Pacific North Forests: 1972-1991

NASA Technical Reports Server (NTRS)

Wallin, David O.; Cohen, Warren B.; Bradshaw, G. A.; Spies, T. A.; Hansen, A.; Huff, M. H.; Lehmkuhl, J. F.; Raphael, M. G.; Ripple, W. J.

1998-01-01

While there is widespread recognition of the importance of preserving biological diversity there is considerable uncertainty about how to map current patterns of diversity and monitor changes through time. Ground-based approaches are impractical for examining regional patterns of biological diversity, for monitoring change, and they may actually overlook important higher-order phenomena. Thus, there is a critical need for innovative techniques to examine land-use effects on biological diversity at the landscape and regional scales. In this project, we have used satellite-based remote sensing to examine land-use effects on forest ecosystems in the Pacific NorthWest region (PNW) of the U.S.A. Rates and patterns of forest change throughout the region were quantified for the period from 1972 to 1993. This information was then used to map changes in the abundance and distribution of potential habitat for selected vertebrate species. The results of this project will be useful for identifying "keystone" stands that are important in maintaining habitat connectivity at the regional scale and for evaluating the impact of future land-use on vertebrate diversity throughout the region. The approaches developed here will also be useful in other forested regions throughout the world.

Three new endemic species of Epictia Gray, 1845 (Serpentes: Leptotyphlopidae) from the dry forest of northwestern Peru.

PubMed

Koch, Claudia; Venegas, Pablo J; Böhme, Wolfgang

2015-06-02

Three new blind snake species of the genus Epictia are described based on material collected in the Peruvian Regions Amazonas, Cajamarca and La Libertad. All three species are well differentiated from all congeners based on characteristics of their morphology and coloration. They share 10 scale rows around the middle of the tail and possess two supralabials with the anterior one in broad contact with the supraocular. Epictia septemlineata sp. nov. has 16 subcaudal scales, 257 mid-dorsal scale rows, a yellowish-white rostral, and a black terminal spine. Epictia vanwallachi sp. nov. exhibits 16 subcaudals, 188 mid-dorsal scale rows, a grayish-brown rostral, and a yellow terminal spine. Epictia antoniogarciai sp. nov. features 14-18 subcaudals, 195-208 mid-dorsal scale rows, a bright yellow or yellowish-white rostral, and the terminal spine and terminal portion of the tail yellow. All three species were collected in the interandean dry forest valleys of the Marañón River and its tributaries. This region is an area of endemism and warrants further attention from systematic and conservation biologists.

Multi-scale Drivers of Variations in Atmospheric Evaporative Demand Based on Observations and Physically-based Modeling

NASA Astrophysics Data System (ADS)

Peng, L.; Sheffield, J.; Li, D.

2015-12-01

Evapotranspiration (ET) is a key link between the availability of water resources and climate change and climate variability. Variability of ET has important environmental and socioeconomic implications for managing hydrological hazards, food and energy production. Although there have been many observational and modeling studies of ET, how ET has varied and the drivers of the variations at different temporal scales remain elusive. Much of the uncertainty comes from the atmospheric evaporative demand (AED), which is the combined effect of radiative and aerodynamic controls. The inconsistencies among modeled AED estimates and the limited observational data may originate from multiple sources including the limited time span and uncertainties in the data. To fully investigate and untangle the intertwined drivers of AED, we present a spectrum analysis to identify key controls of AED across multiple temporal scales. We use long-term records of observed pan evaporation for 1961-2006 from 317 weather stations across China and physically-based model estimates of potential evapotranspiration (PET). The model estimates are based on surface meteorology and radiation derived from reanalysis, satellite retrievals and station data. Our analyses show that temperature plays a dominant role in regulating variability of AED at the inter-annual scale. At the monthly and seasonal scales, the primary control of AED shifts from radiation in humid regions to humidity in dry regions. Unlike many studies focusing on the spatial pattern of ET drivers based on a traditional supply and demand framework, this study underlines the importance of temporal scales when discussing controls of ET variations.

Axisymmetric computational fluid dynamics analysis of Saturn V/S1-C/F1 nozzle and plume

NASA Technical Reports Server (NTRS)

Ruf, Joseph H.

1993-01-01

An axisymmetric single engine Computational Fluid Dynamics calculation of the Saturn V/S 1-C vehicle base region and F1 engine plume is described. There were two objectives of this work, the first was to calculate an axisymmetric approximation of the nozzle, plume and base region flow fields of S1-C/F1, relate/scale this to flight data and apply this scaling factor to a NLS/STME axisymmetric calculations from a parallel effort. The second was to assess the differences in F1 and STME plume shear layer development and concentration of combustible gases. This second piece of information was to be input/supporting data for assumptions made in NLS2 base temperature scaling methodology from which the vehicle base thermal environments were being generated. The F1 calculations started at the main combustion chamber faceplate and incorporated the turbine exhaust dump/nozzle film coolant. The plume and base region calculations were made for ten thousand feet and 57 thousand feet altitude at vehicle flight velocity and in stagnant freestream. FDNS was implemented with a 14 species, 28 reaction finite rate chemistry model plus a soot burning model for the RP-1/LOX chemistry. Nozzle and plume flow fields are shown, the plume shear layer constituents are compared to a STME plume. Conclusions are made about the validity and status of the analysis and NLS2 vehicle base thermal environment definition methodology.

A Land System representation for global assessments and land-use modeling.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2012-10-01

Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.

A new multi-scale geomorphological landscape GIS for the Netherlands

NASA Astrophysics Data System (ADS)

Weerts, Henk; Kosian, Menne; Baas, Henk; Smit, Bjorn

2013-04-01

At present, the Cultural Heritage Agency of the Netherlands is developing a nationwide landscape Geographical Information System (GIS). In this new conceptual approach, the Agency puts together several multi-scale landscape classifications in a GIS. The natural physical landscapes lie at the basis of this GIS, because these landscapes provide the natural boundary conditions for anthropogenic. At the local scale a nationwide digital geomorphological GIS is available in the Netherlands. This map, that was originally mapped at 1:50,000 from the late 1970's to the 1990's, is based on geomorphometrical (observable and measurable in the field), geomorphological and, lithological and geochronological criteria. When used at a national scale, the legend of this comprehensive geomorphological map is very complex which hampers use in e.g. planning practice or predictive archaeology. At the national scale several landscape classifications have been in use in the Netherlands since the early 1950's, typically ranging in the order of 10 -15 landscape units for the entire country. A widely used regional predictive archaeological classification has 13 archaeo-landscapes. All these classifications have been defined "top-down" and their actual content and boundaries have only been broadly defined. Thus, these classifications have little or no meaning at a local scale. We have tried to combine the local scale with the national scale. To do so, we first defined national physical geographical regions based on the new 2010 national geological map 1:500,000. We also made sure there was a reference with the European LANMAP2 classification. We arrived at 20 landscape units at the national scale, based on (1) genesis, (2) large-scale geomorphology, (3) lithology of the shallow sub-surface and (4) age. These criteria that were chosen because the genesis of the landscape largely determines its (scale of) morphology and lithology that in turn determine hydrological conditions. All together, they define the natural boundary conditions for anthropogenic use. All units have been defined, mapped and described based on these criteria. This enables the link with the European LANMAP2 GIS. The unit "Till-plateau sand region" for instance runs deep into Germany and even Poland. At the local scale, the boundaries of the national units can be defined and precisely mapped by linking them to the 1:50,000 geomorphological map polygons. Each national unit consists of a typical assemblage of local geomorphological units. So, the newly developed natural physical landscape map layer can be used from the local to the European scale.

Regional contingencies in the relationship between aboveground biomass and litter in the world’s grasslands

Treesearch

L.R. O' Halloran; E.T. Borer; E.W. Seabloom; A.S. MacDougall; E.E. Cleland; R.L. McCulley; S. Hobbie; S. Harpole; N.M. DeCrappeo; C.-J. Chu; J.D. Bakker; K.F. Davies; G. Du; J. Firn; N. Hagenah; K.S. Hofmockel; J.M.H. Knops; W. Li; B.A. Melbourne; J.W. Morgan; J.L. Orrock; S.M. Prober; C.J. Stevens

2013-01-01

Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a...

SMALL-SCALE FUEL ALCOHOL PRODUCTION TO MEET UNIVERSITY VEHICLE FUEL NEEDS AND PROMOTE REGIONAL SUSTAINABLE DEVELOPMENT

EPA Science Inventory

1. The small scale sweet sorghum ethanol production system in Iowa has good potential for development based on an economic analysis with rates of return ranging from 12% to 32 % for ethanol prices ranging from $1.66/gal to $2.20/gal. A scale of 300 acres (121 ha) for produ...

2. Temporal change in forest fragmentation at multiple scales

   Treesearch

   J.D. Wickham; K.H. Riitters; T.G. Wade; J.W. Coulston

   2007-01-01

   Previous studies of temporal changes in fragmentation have focused almost exclusively on patch and edge statistics, which might not detect changes in the spatial scale at which forest occurs in or dominates the landscape. We used temporal land-cover data for the Chesapeake Bay region and the state of New Jersey to compare patch-based and area–density scaling measures...

3. Moss and lichen cover mapping at local and regional scales in the boreal forest ecosystem of central Canada

   USGS Publications Warehouse

   Rapalee, G.; Steyaert, L.T.; Hall, F.G.

   2001-01-01

   Mosses and lichens are important components of boreal landscapes [Vitt et al., 1994; Bubier et al., 1997]. They affect plant productivity and belowground carbon sequestration and alter the surface runoff and energy balance. We report the use of multiresolution satellite data to map moss and lichens over the BOREAS region at a 10 m, 30 m, and 1 km scales. Our moss and lichen classification at the 10 m scale is based on ground observations of associations among soil drainage classes, overstory composition, and cover type among four broad classes of ground cover (feather, sphagnum, and brown mosses and lichens). For our 30 m map, we used field observations of ground cover-overstory associations to map mosses and lichens in the BOREAS southern study area (SSA). To scale up to a 1 km (AVHRR) moss map of the BOREAS region, we used the TM SSA mosaics plus regional field data to identify AVHRR overstory-ground cover associations. We found that: 1) ground cover, overstory composition and density are highly correlated, permitting inference of moss and lichen cover from satellite-based land cover classifications; 2) our 1 km moss map reveals that mosses dominate the boreal landscape of central Canada, thereby a significant factor for water, energy, and carbon modeling; 3) TM and AVHRR moss cover maps are comparable; 4) satellite data resolution is important; particularly in detecting the smaller wetland features, lakes, and upland jack pine sites; and 5) distinct regional patterns of moss and lichen cover correspond to latitudinal and elevational gradients. Copyright 2001 by the American Geophysical Union.

4. Temporal analysis of intratumoral metabolic heterogeneity characterized by textural features in cervical cancer.

   PubMed

   Yang, Fei; Thomas, Maria A; Dehdashti, Farrokh; Grigsby, Perry W

   2013-05-01

   The aim of this pilot study was to explore heterogeneity in the temporal behavior of intratumoral [(18)F]fluorodeoxyglucose (FDG) accumulation at a regional scale in patients with cervical cancer undergoing chemoradiotherapy. Included in the study were 20 patients with FIGO stages IB1 to IVA cervical cancer treated with combined chemoradiotherapy. Patients underwent FDG PET/CT before treatment, during weeks 2 and 4 of treatment, and 12 weeks after completion of therapy. Patients were classified based on response to therapy as showing a complete metabolic response (CMR), a partial metabolic response (PMR), or residual disease and the development of new disease (NEW). Based on the presence of residual primary tumor following therapy, patients were divided into two groups, CMR and PMR/NEW. Temporal profiles of intratumoral FDG heterogeneity as characterized by textural features at a regional scale were assessed and compared with those of the standardized uptake value (SUV) indices (SUVmax and SUVmean) within the context of differentiating response groups. Textural features at a regional scale with emphasis on characterizing contiguous regions of high uptake in tumors decreased significantly with time (P < 0.001) in the CMR group, while features describing contiguous regions of low uptake along with those measuring the nonuniformity of contiguous isointense regions in tumors exhibited significant temporal changes in the PMR/NEW group (P < 0.03) but showed no persistent trends with time. Both SUV indices showed significant changes during the course of the disease in both patient groups (P < 0.001 for SUVmax and SUVmean in the CMR group; P = 0.0109 and 0.0136, respectively, for SUVmax and SUVmean in the PMR/NEW group), and also decreased at a constant rate in the CMR group and decreased up to the 4th week of treatment and then increased in the PMR/NEW group. The temporal changes in the heterogeneity of intratumoral FDG distribution characterized at a regional scale using image-based textural features may provide an adjunctive or alternative option for understanding tumor response to chemoradiotherapy and interpreting FDG accumulation dynamics in patients with malignant cervical tumors during the course of the disease.

Evolution of natural history information in the 21st century – developing an integrated framework for biological and geographical data

USGS Publications Warehouse

Reusser, Deborah A.; Lee, Henry

2011-01-01

Threats to marine and estuarine species operate over many spatial scales, from nutrient enrichment at the watershed/estuarine scale to invasive species and climate change at regional and global scales. To help address research questions across these scales, we provide here a standardized framework for a biogeographical information system containing queriable biological data that allows extraction of information on multiple species, across a variety of spatial scales based on species distributions, natural history attributes and habitat requirements. As scientists shift from research on localized impacts on individual species to regional and global scale threats, macroecological approaches of studying multiple species over broad geographical areas are becoming increasingly important. The standardized framework described here for capturing and integrating biological and geographical data is a critical first step towards addressing these macroecological questions and we urge organizations capturing biogeoinformatics data to consider adopting this framework.

Evaluation of representativeness of near-surface winds in station measurements, global and regional reanalysis for Germany

NASA Astrophysics Data System (ADS)

Kaspar, Frank; Kaiser-Weiss, Andrea K.; Heene, Vera; Borsche, Michael; Keller, Jan

2015-04-01

Within the preparation activities for a European COPERNICUS Climate Change Service (C3S) several ongoing research projects analyse the potential of global and regional model-based climate reanalyses for applications. A user survey in the FP7-project CORE-CLIMAX revealed that surface wind (10 m) is among the most frequently used parameters of global reanalysis products. The FP7 project UERRA (Uncertainties in Ensembles of Regional Re-Analysis) has the focus on regional European reanalysis and the associated uncertainties, also from a user perspective. Especially in the field of renewable energy planning and production there is a need for climatological information across all spatial scales, i.e., from climatology at a certain site to the spatial scale of national or continental renewable energy production. Here, we focus on a comparison of wind measurements of the Germany's meteorological service (Deutscher Wetterdienst, DWD) with global reanalyses of ECWMF and a regional reanalysis for Europe based on DWD's NWP-model COSMO (performed by the Hans-Ertel-Center for Weather Research, University of Bonn). Reanalyses can provide valuable additional information on larger scale variability, e.g. multi-annual variation over Germany. However, changes in the observing system, model errors and biases have to be carefully considered. On the other hand, the ground-based observation networks partly suffer from change of the station distribution, changes in instrumentation, measurements procedures and quality control as well as local changes which might modify their spatial representativeness. All these effects might often been unknown or hard to characterize, although plenty of the meta-data information has been recorded for the German stations. One focus of the presentation will be the added-value of the regional reanalysis.

Detecting the Reconnection Electron Diffusion Regions in Magnetospheric MultiScale mission high resolution data

NASA Astrophysics Data System (ADS)

Shimoda, E.; Eriksson, S.; Ahmadi, N.; Ergun, R.; Wilder, F. D.; Goodrich, K.

2017-12-01

The Magnetospheric Multi-Scale (MMS) mission resolves the small-scale structure of the Reconnection Electron Diffusion Regions (EDRs) using four spacecraft. We have surveyed two years of MMS data to find the candidates for the EDRs. We searched all the high-resolution segments when Fast Plasma Investigation (FPI) instrument was on. The search criteria are based on measuring the dissipation rate, agyrotropy, a reversal in jet velocity and magnetic field. Once these events were found for MMS1 data, the burst period for the other spacecraft was analyzed. We present our results of the best possible EDR candidates.

Havens: Explicit Reliable Memory Regions for HPC Applications

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

Hukerikar, Saurabh; Engelmann, Christian

2016-01-01

Supporting error resilience in future exascale-class supercomputing systems is a critical challenge. Due to transistor scaling trends and increasing memory density, scientific simulations are expected to experience more interruptions caused by transient errors in the system memory. Existing hardware-based detection and recovery techniques will be inadequate to manage the presence of high memory fault rates. In this paper we propose a partial memory protection scheme based on region-based memory management. We define the concept of regions called havens that provide fault protection for program objects. We provide reliability for the regions through a software-based parity protection mechanism. Our approach enablesmore » critical program objects to be placed in these havens. The fault coverage provided by our approach is application agnostic, unlike algorithm-based fault tolerance techniques.« less

Serial grouping of 2D-image regions with object-based attention in humans

PubMed Central

Jeurissen, Danique; Self, Matthew W; Roelfsema, Pieter R

2016-01-01

After an initial stage of local analysis within the retina and early visual pathways, the human visual system creates a structured representation of the visual scene by co-selecting image elements that are part of behaviorally relevant objects. The mechanisms underlying this perceptual organization process are only partially understood. We here investigate the time-course of perceptual grouping of two-dimensional image-regions by measuring the reaction times of human participants and report that it is associated with the gradual spread of object-based attention. Attention spreads fastest over large and homogeneous areas and is slowed down at locations that require small-scale processing. We find that the time-course of the object-based selection process is well explained by a 'growth-cone' model, which selects surface elements in an incremental, scale-dependent manner. We discuss how the visual cortical hierarchy can implement this scale-dependent spread of object-based attention, leveraging the different receptive field sizes in distinct cortical areas. DOI: http://dx.doi.org/10.7554/eLife.14320.001 PMID:27291188

Comparison of local- to regional-scale estimates of ground-water recharge in Minnesota, USA

USGS Publications Warehouse

Delin, G.N.; Healy, R.W.; Lorenz, D.L.; Nimmo, J.R.

2007-01-01

Regional ground-water recharge estimates for Minnesota were compared to estimates made on the basis of four local- and basin-scale methods. Three local-scale methods (unsaturated-zone water balance, water-table fluctuations (WTF) using three approaches, and age dating of ground water) yielded point estimates of recharge that represent spatial scales from about 1 to about 1000 m2. A fourth method (RORA, a basin-scale analysis of streamflow records using a recession-curve-displacement technique) yielded recharge estimates at a scale of 10–1000s of km2. The RORA basin-scale recharge estimates were regionalized to estimate recharge for the entire State of Minnesota on the basis of a regional regression recharge (RRR) model that also incorporated soil and climate data. Recharge rates estimated by the RRR model compared favorably to the local and basin-scale recharge estimates. RRR estimates at study locations were about 41% less on average than the unsaturated-zone water-balance estimates, ranged from 44% greater to 12% less than estimates that were based on the three WTF approaches, were about 4% less than the age dating of ground-water estimates, and were about 5% greater than the RORA estimates. Of the methods used in this study, the WTF method is the simplest and easiest to apply. Recharge estimates made on the basis of the UZWB method were inconsistent with the results from the other methods. Recharge estimates using the RRR model could be a good source of input for regional ground-water flow models; RRR model results currently are being applied for this purpose in USGS studies elsewhere.

A diagnostic model to estimate winds and small-scale drag from Mars Observer PMIRR data

NASA Technical Reports Server (NTRS)

Barnes, J. R.

1993-01-01

Theoretical and modeling studies indicate that small-scale drag due to breaking gravity waves is likely to be of considerable importance for the circulation in the middle atmospheric region (approximately 40-100 km altitude) on Mars. Recent earth-based spectroscopic observations have provided evidence for the existence of circulation features, in particular, a warm winter polar region, associated with gravity wave drag. Since the Mars Observer PMIRR experiment will obtain temperature profiles extending from the surface up to about 80 km altitude, it will be extensively sampling middle atmospheric regions in which gravity wave drag may play a dominant role. Estimating the drag then becomes crucial to the estimation of the atmospheric winds from the PMIRR-observed temperatures. An interative diagnostic model based upon one previously developed and tested with earth satellite temperature data will be applied to the PMIRR measurements to produce estimates of the small-scale zonal drag and three-dimensional wind fields in the Mars middle atmosphere. This model is based on the primitive equations, and can allow for time dependence (the time tendencies used may be based upon those computed in a Fast Fourier Mapping procedure). The small-scale zonal drag is estimated as the residual in the zonal momentum equation; the horizontal winds having first been estimated from the meridional momentum equation and the continuity equation. The scheme estimates the vertical motions from the thermodynamic equation, and thus needs estimates of the diabatic heating based upon the observed temperatures. The latter will be generated using a radiative model. It is hoped that the diagnostic scheme will be able to produce good estimates of the zonal gravity wave drag in the Mars middle atmosphere, estimates that can then be used in other diagnostic or assimilation efforts, as well as more theoretical studies.

[Estimating medicinal yield of Seutellaria baicalensis in Beijing-Tianjin-Hebei region based on 3S technology].

PubMed

Liu, Jin-xinp; Lu, Heng; Zeng, Yan; Yue, Jian-wei; Meng, Fan-yun; Zhang, Yi-guang

2012-09-01

Resources survey of traditional Chinese medicine and reserves estimation are found to be the most important issues for the protection and utilization of traditional Chinese medicine resources, this paper used multi-spatial resolution remote sensing images (RS) , geographic information systems (GIS) and global positioning system (GPS) , to establish Scutellaria resources survey of 3S data platform. Combined with the traditional field survey methods, small-scale habitat types were established based on different skullcap reserve estimation model, which can estimate reserves of the wild Scutellaria in Beijing-Tianjin-Hebei region and improve the estimation accuracy. It can provide an important parameter for the fourth national survey of traditional Chinese medicine resources and traditional Chinese medicine reserves estimates based on 3S technology by multiple spatial scales model.

Brief communication: Using averaged soil moisture estimates to improve the performances of a regional-scale landslide early warning system

NASA Astrophysics Data System (ADS)

Segoni, Samuele; Rosi, Ascanio; Lagomarsino, Daniela; Fanti, Riccardo; Casagli, Nicola

2018-03-01

We communicate the results of a preliminary investigation aimed at improving a state-of-the-art RSLEWS (regional-scale landslide early warning system) based on rainfall thresholds by integrating mean soil moisture values averaged over the territorial units of the system. We tested two approaches. The simplest can be easily applied to improve other RSLEWS: it is based on a soil moisture threshold value under which rainfall thresholds are not used because landslides are not expected to occur. Another approach deeply modifies the original RSLEWS: thresholds based on antecedent rainfall accumulated over long periods are substituted with soil moisture thresholds. A back analysis demonstrated that both approaches consistently reduced false alarms, while the second approach reduced missed alarms as well.

Analyzing cloud base at local and regional scales to understand tropical montane cloud forest vulnerability to climate change

Treesearch

Ashley E. Van Beusekom; Grizelle Gonzalez; Martha A. Scholl

2017-01-01

The degree to which cloud immersion provides water in addition to rainfall, suppresses transpiration, and sustains tropical montane cloud forests (TMCFs) during rainless periods is not well understood. Climate and land use changes represent a threat to these forests if cloud base altitude rises as a result of regional warming or deforestation. To establish a baseline...

MODELLING OF POLYCHLORINATED-DIOXIN AND -FURAN CONGENER PROFILES FROM MUNICIPAL WASTE COMBUSTION

EPA Science Inventory

The paper discusses a model, based on experimental data, that was developed to describe the profile of polychlorinated dibenzo-p-dioxin (PCDD) and polychlorinated dibenzofuran (PCDF) congeners formed in the duct region of a pilot-scale combustor simulating large-scale municipal w...

Large-scale variation in subsurface stream biofilms: a cross-regional comparison of metabolic function and community similarity.

PubMed

Findlay, S; Sinsabaugh, R L

2006-10-01

We examined bacterial metabolic activity and community similarity in shallow subsurface stream sediments distributed across three regions of the eastern United States to assess whether there were parallel changes in functional and structural attributes at this large scale. Bacterial growth, oxygen consumption, and a suite of extracellular enzyme activities were assayed to describe functional variability. Community similarity was assessed using randomly amplified polymorphic DNA (RAPD) patterns. There were significant differences in streamwater chemistry, metabolic activity, and bacterial growth among regions with, for instance, twofold higher bacterial production in streams near Baltimore, MD, compared to Hubbard Brook, NH. Five of eight extracellular enzymes showed significant differences among regions. Cluster analyses of individual streams by metabolic variables showed clear groups with significant differences in representation of sites from different regions among groups. Clustering of sites based on randomly amplified polymorphic DNA banding resulted in groups with generally less internal similarity although there were still differences in distribution of regional sites. There was a marginally significant (p = 0.09) association between patterns based on functional and structural variables. There were statistically significant but weak (r2 approximately 30%) associations between landcover and measures of both structure and function. These patterns imply a large-scale organization of biofilm communities and this structure may be imposed by factor(s) such as landcover and covariates such as nutrient concentrations, which are known to also cause differences in macrobiota of stream ecosystems.

Spatial scale effect on sediment dynamics in basin-wide floods within a typical agro-watershed: A case study in the hilly loess region of the Chinese Loess Plateau.

PubMed

Zhang, Le-Tao; Li, Zhan-Bin; Wang, Shan-Shan

2016-12-01

Scale issues, which have been extensively studied in the domain of soil erosion, are considerably significant in geomorphologic processes and hydrologic modelling. However, relatively scarce efforts have been made to quantify the spatial scale effect on event-based sediment dynamics in basin-wide floods. To address this issue, sediment-runoff yield data of 44 basin-wide flood events were collected from gauging stations at the Chabagou river basin, a typical agro-basin (unmanaged) in the hilly loess region of the Chinese Loess Plateau. Thus, the spatial scale effect on event-based sediment dynamics was investigated in the basin system across three different spatial scales from sublateral to basin outlet. Results showed that the event-based suspended sediment concentration, as well as the intra- and inter-scale flow-sediment relationships remained spatially constant. Hence, almost all the sediment-laden flows can reach at the detachment-limited maximum concentration across scales, specifically for hyperconcentrated flows. Consequently, limited influence was exerted by upstream sediment-laden flow on downstream sediment output, particularly for major sediment-producing events. However, flood peak discharge instead of total flood runoff amount can better interpret the dynamics of sediment yield across scales. As a composite parameter, the proposed stream energy factor combines flood runoff depth and flood peak discharge, thereby showing more advantages to describe the event-based inter-scale flow-sediment relationship than other flow-related variables. Overall, this study demonstrates the process-specific characteristics of soil erosion by water flows in the basin system. Therefore, event-based sediment control should be oriented by the process to cut off the connectivity of hyperconcentrated flows and redistribute the erosive energy of flowing water in terms of temporality and spatiality. Furthermore, evaluation of soil conservation benefits should be based on the process of runoff regulation to comprehensively assess the efficiency of anti-erosion strategies in sediment control at the basin scale. Copyright © 2016. Published by Elsevier B.V.

Air quality in the mid-21st century for the city of Paris under two climate scenarios; from the regional to local scale

NASA Astrophysics Data System (ADS)

Markakis, K.; Valari, M.; Colette, A.; Sanchez, O.; Perrussel, O.; Honore, C.; Vautard, R.; Klimont, Z.; Rao, S.

2014-07-01

Ozone and PM2.5 concentrations over the city of Paris are modeled with the CHIMERE air-quality model at 4 km × 4 km horizontal resolution for two future emission scenarios. A high-resolution (1 km × 1 km) emission projection until 2020 for the greater Paris region is developed by local experts (AIRPARIF) and is further extended to year 2050 based on regional-scale emission projections developed by the Global Energy Assessment. Model evaluation is performed based on a 10-year control simulation. Ozone is in very good agreement with measurements while PM2.5 is underestimated by 20% over the urban area mainly due to a large wet bias in wintertime precipitation. A significant increase of maximum ozone relative to present-day levels over Paris is modeled under the "business-as-usual" scenario (+7 ppb) while a more optimistic "mitigation" scenario leads to a moderate ozone decrease (-3.5 ppb) in year 2050. These results are substantially different to previous regional-scale projections where 2050 ozone is found to decrease under both future scenarios. A sensitivity analysis showed that this difference is due to the fact that ozone formation over Paris at the current urban-scale study is driven by volatile organic compound (VOC)-limited chemistry, whereas at the regional-scale ozone formation occurs under NOx-sensitive conditions. This explains why the sharp NOx reductions implemented in the future scenarios have a different effect on ozone projections at different scales. In rural areas, projections at both scales yield similar results showing that the longer timescale processes of emission transport and ozone formation are less sensitive to model resolution. PM2.5 concentrations decrease by 78% and 89% under business-as-usual and mitigation scenarios, respectively, compared to the present-day period. The reduction is much more prominent over the urban part of the domain due to the effective reductions of road transport and residential emissions resulting in the smoothing of the large urban increment modeled in the control simulation.

GRACE storage-runoff hystereses reveal the dynamics of ...

EPA Pesticide Factsheets

Watersheds function as integrated systems where climate and geology govern the movement of water. In situ instrumentation can provide local-scale insights into the non-linear relationship between streamflow and water stored in a watershed as snow, soil moisture, and groundwater. However, there is a poor understanding of these processes at the regional scale—primarily because of our inability to measure water stores and fluxes in the subsurface. Now NASA’s Gravity Recovery and Climate Experiment (GRACE) satellites quantify changes in the amount of water stored across and through the Earth, providing measurements of regional hydrologic behavior. Here we apply GRACE data to characterize for the first time how regional watersheds function as simple, dynamic systems through a series of hysteresis loops. While the physical processes underlying the loops are inherently complex, the vertical integration of terrestrial water in the GRACE signal provides process-based insights into the dynamic and non-linear function of regional-scale watersheds. We use this process-based understanding with GRACE data to effectively forecast seasonal runoff (mean R2 of 0.91) and monthly runoff (mean R2 of 0.77) in three regional-scale watersheds (>150,000 km2) of the Columbia River Basin, USA. Data from the Gravity Recovery and Climate Experiment (GRACE) satellites provide a novel dataset for understanding changes in the amount of water stored across and through the surface of the Ear

Wave particle interactions in Jupiter's magnetosphere: Implications for auroral and magnetospheric particle distributions

NASA Astrophysics Data System (ADS)

Saur, Joachim; Schreiner, Anne; Barry, Mauk; Clark, George; Kollman, Peter

2017-04-01

We investigate the occurrence and the role of wave particle interaction processes, i.e., Landau and cyclotron damping, in Jupiter's magnetosphere. Therefore we calculate kinetic length and temporal scales, which we cross-compare at various regions within Jupiter's magnetosphere. Based on these scales, we investigate the roles of possible wave particle mechanisms in each region, e.g., Jupiter's plasma sheet, the auroral acceleration region and the polar ionosphere. We thereby consider that the magnetospheric regions are coupled through convective transport, Alfven and other wave modes. We particularly focus on the role of kinetic Alfven waves in contributing to Jupiter's aurora. Our results will aid the interpretation of particle distribution functions measured by the JEDI instrument onboard the JUNO spacecraft.

Exploring the Links in Monthly to Decadal Variability of the Atmospheric Water Balance Over the Wettest Regions in ERA-20C

NASA Astrophysics Data System (ADS)

Nogueira, M.

2017-10-01

Monthly-to-decadal variability of the regional precipitation over Intertropical Convergence Zone and north-Atlantic and north-Pacific storm tracks was investigated using ERA-20C reanalysis. Satellite-based precipitation (P) and evaporation (E) climatological patterns were well reproduced by ERA-20C. Regional P and E monthly time series displayed 20% differences, but these decreased rapidly with time scale ( 10% at yearly time scales). Spectral analysis showed good scale-by-scale statistical agreement between ERA-20C and observations. Using ERA-Interim showed no improvement despite the much wider range of information assimilated (including satellites). Remarkably high Detrended Cross-Correlation Analysis coefficients (ρDCCA > 0.7 and often ρDCCA > 0.9) revealed tight links between the nonperiodic variability of P, moisture divergence (DIV), and pressure velocity (ω) at monthly-to-decadal time scales over all the wet regions. In contrast, ρDCCA was essentially nonsignificant between nonperiodic P and E or sea surface temperature (SST). Thus, the nonperiodic monthly-to-decadal variability of precipitation in these regions is almost fully controlled by dynamics and not by local E or SST (suggested by Clausius-Clapeyron relation). Analysis of regional nonperiodic standard deviations and power spectra (and respective spectral exponents, β) provided further robustness to this conclusion. Finally, clear transitions in β for P, DIV, and ω between tropical and storm track regions were found. The latter is dominated by transient storms, with energy accumulation at synoptic scales and β < 0.1 at monthly-to-decadal time scales, implying that variability and information creation decrease rapidly with time scale. Larger β values (0.2 to 0.4) were found in the tropics, implying longer-range autocorrelations and slower decreasing variability and information creation with time scale, consistent with the important forcing from internal modes of variability (e.g., El Niño-Southern Oscillation).

Advances in Landslide Hazard Forecasting: Evaluation of Global and Regional Modeling Approach

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia B.; Adler, Robert; Hone, Yang; Kumar, Sujay; Peters-Lidard, Christa; Lerner-Lam, Arthur

2010-01-01

A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that exhibit a high potential for landslide activity by combining a calculation of landslide susceptibility with satellite-derived rainfall estimates. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale landslide forecasting efforts, it requires several modifications before it can be fully realized as an operational tool. The evaluation finds that the landslide forecasting may be more feasible at a regional scale. This study draws upon a prior work's recommendations to develop a new approach for considering landslide susceptibility and forecasting at the regional scale. This case study uses a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America: Guatemala, Honduras, EI Salvador and Nicaragua. A regional susceptibility map is calculated from satellite and surface datasets using a statistical methodology. The susceptibility map is tested with a regional rainfall intensity-duration triggering relationship and results are compared to global algorithm framework for the Hurricane Mitch event. The statistical results suggest that this regional investigation provides one plausible way to approach some of the data and resolution issues identified in the global assessment, providing more realistic landslide forecasts for this case study. Evaluation of landslide hazards for this extreme event helps to identify several potential improvements of the algorithm framework, but also highlights several remaining challenges for the algorithm assessment, transferability and performance accuracy. Evaluation challenges include representation errors from comparing susceptibility maps of different spatial resolutions, biases in event-based landslide inventory data, and limited nonlandslide event data for more comprehensive evaluation. Additional factors that may improve algorithm performance accuracy include incorporating additional triggering factors such as tectonic activity, anthropogenic impacts and soil moisture into the algorithm calculation. Despite these limitations, the methodology presented in this regional evaluation is both straightforward to calculate and easy to interpret, making results transferable between regions and allowing findings to be placed within an inter-comparison framework. The regional algorithm scenario represents an important step in advancing regional and global-scale landslide hazard assessment and forecasting.

Spontaneous alterations of regional brain activity in patients with adult generalized anxiety disorder

PubMed Central

Xia, Likun; Li, Shumei; Wang, Tianyue; Guo, Yaping; Meng, Lihong; Feng, Yunping; Cui, Yu; Wang, Fan; Ma, Jian; Jiang, Guihua

2017-01-01

Objective We aimed to examine how spontaneous brain activity might be related to the pathophysiology of generalized anxiety disorder (GAD). Patients and methods Using resting-state functional MRI, we examined spontaneous regional brain activity in 31 GAD patients (mean age, 36.87±9.16 years) and 36 healthy control participants (mean age, 39.53±8.83 years) matched for age, education, and sex from December 2014 to October 2015. We performed a two-sample t-test on the voxel-based analysis of the regional homogeneity (ReHo) maps. We used Pearson correlation analysis to compare scores from the Hamilton Anxiety Rating Scale, Hamilton Depression Rating Scale, State–Trait Anxiety Scale-Trait Scale, and mean ReHo values. Results We found abnormal spontaneous activity in multiple regions of brain in GAD patients, especially in the sensorimotor cortex and emotional regions. GAD patients showed decreased ReHo values in the right orbital middle frontal gyrus, left anterior cingulate cortex, right middle frontal gyrus, and bilateral supplementary motor areas, with increased ReHo values in the left middle temporal gyrus, left superior temporal gyrus, and right superior occipital gyrus. The ReHo value of the left middle temporal gyrus correlated positively with the Hamilton Anxiety Rating Scale scores. Conclusion These results suggest that altered local synchronization of spontaneous brain activity may be related to the pathophysiology of GAD. PMID:28790831

Warm Mediterranean mid-Holocene summers inferred from fossil midge assemblages

NASA Astrophysics Data System (ADS)

Samartin, Stéphanie; Heiri, Oliver; Joos, Fortunat; Renssen, Hans; Franke, Jörg; Brönnimann, Stefan; Tinner, Willy

2017-02-01

Understanding past climate trends is key for reliable projections of global warming and associated risks and hazards. Uncomfortably large discrepancies between vegetation-based summer temperature reconstructions (mainly based on pollen) and climate model results have been reported for the current interglacial, the Holocene. For the Mediterranean region these reconstructions indicate cooler-than-present mid-Holocene summers, in contrast with expectations based on climate models and long-term changes in summer insolation. We present new quantitative and replicated Holocene summer temperature reconstructions based on fossil chironomid midges from the northern central Mediterranean region. The Holocene thermal maximum is reconstructed 9,000-5,000 years ago and estimated to have been 1-2 °C warmer in mean July temperature than the recent pre-industrial period, consistent with glacier and marine records, and with transient climate model runs. This combined evidence implies that widely used pollen-based summer temperature reconstructions in the Mediterranean area are significantly biased by precipitation or other forcings such as early land use. Our interpretation can resolve the previous discrepancy between climate models and quantitative palaeotemperature records for millennial-scale Holocene summer temperature trends in the Mediterranean region. It also suggests that pollen-based evidence for cool mid-Holocene summers in other semi-arid to arid regions of the Northern Hemisphere may have to be reconsidered, with potential implications for global-scale reconstructions.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Earthquake Hazard and Risk Assessment based on Unified Scaling Law for Earthquakes: Altai-Sayan Region

NASA Astrophysics Data System (ADS)

Kossobokov, V. G.; Nekrasova, A.

2017-12-01

We continue applying the general concept of seismic risk analysis in a number of seismic regions worldwide by constructing regional seismic hazard maps based on morphostructural analysis, pattern recognition, and the Unified Scaling Law for Earthquakes, USLE, which generalizes the Gutenberg-Richter relationship making use of naturally fractal distribution of earthquake sources of different size in a seismic region. The USLE stands for an empirical relationship log10N(M, L) = A + B·(5 - M) + C·log10L, where N(M, L) is the expected annual number of earthquakes of a certain magnitude M within an seismically prone area of linear dimension L. We use parameters A, B, and C of USLE to estimate, first, the expected maximum credible magnitude in a time interval at seismically prone nodes of the morphostructural scheme of the region under study, then map the corresponding expected ground shaking parameters (e.g. peak ground acceleration, PGA, or macro-seismic intensity etc.). After a rigorous testing against the available seismic evidences in the past (usually, the observed instrumental PGA or the historically reported macro-seismic intensity), such a seismic hazard map is used to generate maps of specific earthquake risks for population, cities, and infrastructures (e.g., those based on census of population, buildings inventory, etc.). This, USLE based, methodology of seismic hazard and risks assessment is applied to the territory of Altai-Sayan Region, of Russia. The study supported by the Russian Science Foundation Grant No. 15-17-30020.

Modelling the elements of country vulnerability to earthquake disasters.

PubMed

Asef, M R

2008-09-01

Earthquakes have probably been the most deadly form of natural disaster in the past century. Diversity of earthquake specifications in terms of magnitude, intensity and frequency at the semicontinental scale has initiated various kinds of disasters at a regional scale. Additionally, diverse characteristics of countries in terms of population size, disaster preparedness, economic strength and building construction development often causes an earthquake of a certain characteristic to have different impacts on the affected region. This research focuses on the appropriate criteria for identifying the severity of major earthquake disasters based on some key observed symptoms. Accordingly, the article presents a methodology for identification and relative quantification of severity of earthquake disasters. This has led to an earthquake disaster vulnerability model at the country scale. Data analysis based on this model suggested a quantitative, comparative and meaningful interpretation of the vulnerability of concerned countries, and successfully explained which countries are more vulnerable to major disasters.

The pyramid system for multiscale raster analysis

USGS Publications Warehouse

De Cola, L.; Montagne, N.

1993-01-01

Geographical research requires the management and analysis of spatial data at multiple scales. As part of the U.S. Geological Survey's global change research program a software system has been developed that reads raster data (such as an image or digital elevation model) and produces a pyramid of aggregated lattices as well as various measurements of spatial complexity. For a given raster dataset the system uses the pyramid to report: (1) mean, (2) variance, (3) a spatial autocorrelation parameter based on multiscale analysis of variance, and (4) a monofractal scaling parameter based on the analysis of isoline lengths. The system is applied to 1-km digital elevation model (DEM) data for a 256-km2 region of central California, as well as to 64 partitions of the region. PYRAMID, which offers robust descriptions of data complexity, also is used to describe the behavior of topographic aspect with scale. ?? 1993.

Propagation of Intra-Seasonal Tropical Oscillations (PISTON)

NASA Astrophysics Data System (ADS)

Moum, J. N.

2017-12-01

During monsoon season over the South China Sea and Philippines, weather varies on the subseasonal time scale. Disturbances of the "boreal summer intraseasonal oscillation" (BSISO) move north and east across the region over periods of weeks. These disturbances are strongly conditioned by the complex geography of the region. The diurnal cycle in convection over islands and adjacent coastal seas is strong. Air-sea interaction is modulated by ocean stratification and local circulation patterns that are themselves complex and diurnally varying. The multiple pathways and space-time scales in the regional ocean-atmosphere-land system make prediction on subseasonal to seasonal time scales challenging. The PISTON field campaign targets the west coast of Luzon in August/September 2018. It includes ship-based, moored and land-based measurements, a significant modeling effort and coordinates with the Philippine SALICA program (Sea Air Land Interactions in the Context of Archipelagos) and the aircraft-based, NASA-funded CAMP2EX campaign (Cloud and Aerosol Monsoonal Processes-Philippines Experiment). The diurnal cycle and its interaction with the BSISO are primary targets for PISTON. Key questions are: how heat is stored and released in the upper ocean on intraseasonal time scales; how that heat storage interacts with atmospheric convection; and what role it plays in BSISO maintenance and propagation. Key processes include land-sea breezes, orographic influence on convection, river discharge to coastal oceans, gravity waves, diurnal warm layers, internal tides, and a buoyancy-driven northward coastal current. As intraseasonal disturbances approach the region, the presence of islands, with their low surface heat capacity, mountains, inhomogeneous distribution of urban/vegetation/soil, and strong diurnal cycle disrupts the air-sea heat exchange that sustains the BSISO over the ocean, confounding prediction models in which these processes are inadequately represented. Along with upscale influences, PISTON seeks to advance our understanding of how large scale atmospheric circulation variability over the South China Sea, related to the monsoon, BSISO, and convectively coupled waves, modifies the local diurnal cycle, synoptic systems, and air sea interaction in coastal regions and nearby open seas.

Saliency image of feature building for image quality assessment

NASA Astrophysics Data System (ADS)

Ju, Xinuo; Sun, Jiyin; Wang, Peng

2011-11-01

The purpose and method of image quality assessment are quite different for automatic target recognition (ATR) and traditional application. Local invariant feature detectors, mainly including corner detectors, blob detectors and region detectors etc., are widely applied for ATR. A saliency model of feature was proposed to evaluate feasibility of ATR in this paper. The first step consisted of computing the first-order derivatives on horizontal orientation and vertical orientation, and computing DoG maps in different scales respectively. Next, saliency images of feature were built based auto-correlation matrix in different scale. Then, saliency images of feature of different scales amalgamated. Experiment were performed on a large test set, including infrared images and optical images, and the result showed that the salient regions computed by this model were consistent with real feature regions computed by mostly local invariant feature extraction algorithms.

Identification of Flood Reactivity Regions via the Functional Clustering of Hydrographs

NASA Astrophysics Data System (ADS)

Brunner, Manuela I.; Viviroli, Daniel; Furrer, Reinhard; Seibert, Jan; Favre, Anne-Catherine

2018-03-01

Flood hydrograph shapes contain valuable information on the flood-generation mechanisms of a catchment. To make good use of this information, we express flood hydrograph shapes as continuous functions using a functional data approach. We propose a clustering approach based on functional data for flood hydrograph shapes to identify a set of representative hydrograph shapes on a catchment scale and use these catchment-specific sets of representative hydrographs to establish regions of catchments with similar flood reactivity on a regional scale. We applied this approach to flood samples of 163 medium-size Swiss catchments. The results indicate that three representative hydrograph shapes sufficiently describe the hydrograph shape variability within a catchment and therefore can be used as a proxy for the flood behavior of a catchment. These catchment-specific sets of three hydrographs were used to group the catchments into three reactivity regions of similar flood behavior. These regions were not only characterized by similar hydrograph shapes and reactivity but also by event magnitudes and triggering event conditions. We envision these regions to be useful in regionalization studies, regional flood frequency analyses, and to allow for the construction of synthetic design hydrographs in ungauged catchments. The clustering approach based on functional data which establish these regions is very flexible and has the potential to be extended to other geographical regions or toward the use in climate impact studies.

Farmland Drought Evaluation Based on the Assimilation of Multi-Temporal Multi-Source Remote Sensing Data into AquaCrop Model

NASA Astrophysics Data System (ADS)

Yang, Guijun; Yang, Hao; Jin, Xiuliang; Pignatti, Stefano; Casa, Faffaele; Silverstro, Paolo Cosmo

2016-08-01

Drought is the most costly natural disasters in China and all over the world. It is very important to evaluate the drought-induced crop yield losses and further improve water use efficiency at regional scale. Firstly, crop biomass was estimated by the combined use of Synthetic Aperture Radar (SAR) and optical remote sensing data. Then the estimated biophysical variable was assimilated into crop growth model (FAO AquaCrop) by the Particle Swarm Optimization (PSO) method from farmland scale to regional scale.At farmland scale, the most important crop parameters of AquaCrop model were determined to reduce the used parameters in assimilation procedure. The Extended Fourier Amplitude Sensitivity Test (EFAST) method was used for assessing the contribution of different crop parameters to model output. Moreover, the AquaCrop model was calibrated using the experiment data in Xiaotangshan, Beijing.At regional scale, spatial application of our methods were carried out and validated in the rural area of Yangling, Shaanxi Province, in 2014. This study will provide guideline to make irrigation decision of balancing of water consumption and yield loss.

Scaling Up Success: Lessons Learned from Technology-Based Educational Improvement

ERIC Educational Resources Information Center

Dede, Chris, Ed.; Honan, James P., Ed.; Peters, Laurence C., Ed.

2005-01-01

Drawing from the information presented at a conference sponsored by the Harvard Graduate School of Education and the Mid-Atlantic Regional Technology in Education Consortium, educators, researchers, and policymakers translate theory into practice to provide a hands-on resource that describes different models for scaling up success. This resource…

Application of Hierarchy Theory to Cross-Scale Hydrologic Modeling of Nutrient Loads

EPA Science Inventory

We describe a model called Regional Hydrologic Modeling for Environmental Evaluation 16 (RHyME²) for quantifying annual nutrient loads in stream networks and watersheds. RHyME² is 17 a cross-scale statistical and process-based water-quality model. The model ...

Anthropogenic-based regional-scale factors most consistently explain plot-level exotic diversity in grasslands

USDA-ARS?s Scientific Manuscript database

Invasion is viewed as a dominant threat to Earth’s biological diversity, but evidence linking the accumulation of exotic species to the simultaneous suppression of native diversity is equivocal, relying heavily on data from studies using different methods and designs. Fine-scale studies often descr...

Automated object-based classification of topography from SRTM data

PubMed Central

Drăguţ, Lucian; Eisank, Clemens

2012-01-01

We introduce an object-based method to automatically classify topography from SRTM data. The new method relies on the concept of decomposing land-surface complexity into more homogeneous domains. An elevation layer is automatically segmented and classified at three scale levels that represent domains of complexity by using self-adaptive, data-driven techniques. For each domain, scales in the data are detected with the help of local variance and segmentation is performed at these appropriate scales. Objects resulting from segmentation are partitioned into sub-domains based on thresholds given by the mean values of elevation and standard deviation of elevation respectively. Results resemble reasonably patterns of existing global and regional classifications, displaying a level of detail close to manually drawn maps. Statistical evaluation indicates that most of classes satisfy the regionalization requirements of maximizing internal homogeneity while minimizing external homogeneity. Most objects have boundaries matching natural discontinuities at regional level. The method is simple and fully automated. The input data consist of only one layer, which does not need any pre-processing. Both segmentation and classification rely on only two parameters: elevation and standard deviation of elevation. The methodology is implemented as a customized process for the eCognition® software, available as online download. The results are embedded in a web application with functionalities of visualization and download. PMID:22485060

Automated object-based classification of topography from SRTM data

NASA Astrophysics Data System (ADS)

Drăguţ, Lucian; Eisank, Clemens

2012-03-01

We introduce an object-based method to automatically classify topography from SRTM data. The new method relies on the concept of decomposing land-surface complexity into more homogeneous domains. An elevation layer is automatically segmented and classified at three scale levels that represent domains of complexity by using self-adaptive, data-driven techniques. For each domain, scales in the data are detected with the help of local variance and segmentation is performed at these appropriate scales. Objects resulting from segmentation are partitioned into sub-domains based on thresholds given by the mean values of elevation and standard deviation of elevation respectively. Results resemble reasonably patterns of existing global and regional classifications, displaying a level of detail close to manually drawn maps. Statistical evaluation indicates that most of classes satisfy the regionalization requirements of maximizing internal homogeneity while minimizing external homogeneity. Most objects have boundaries matching natural discontinuities at regional level. The method is simple and fully automated. The input data consist of only one layer, which does not need any pre-processing. Both segmentation and classification rely on only two parameters: elevation and standard deviation of elevation. The methodology is implemented as a customized process for the eCognition® software, available as online download. The results are embedded in a web application with functionalities of visualization and download.

Application of physical scaling towards downscaling climate model precipitation data

NASA Astrophysics Data System (ADS)

Gaur, Abhishek; Simonovic, Slobodan P.

2018-04-01

Physical scaling (SP) method downscales climate model data to local or regional scales taking into consideration physical characteristics of the area under analysis. In this study, multiple SP method based models are tested for their effectiveness towards downscaling North American regional reanalysis (NARR) daily precipitation data. Model performance is compared with two state-of-the-art downscaling methods: statistical downscaling model (SDSM) and generalized linear modeling (GLM). The downscaled precipitation is evaluated with reference to recorded precipitation at 57 gauging stations located within the study region. The spatial and temporal robustness of the downscaling methods is evaluated using seven precipitation based indices. Results indicate that SP method-based models perform best in downscaling precipitation followed by GLM, followed by the SDSM model. Best performing models are thereafter used to downscale future precipitations made by three global circulation models (GCMs) following two emission scenarios: representative concentration pathway (RCP) 2.6 and RCP 8.5 over the twenty-first century. The downscaled future precipitation projections indicate an increase in mean and maximum precipitation intensity as well as a decrease in the total number of dry days. Further an increase in the frequency of short (1-day), moderately long (2-4 day), and long (more than 5-day) precipitation events is projected.

Soil organic matter dynamics and CO2 fluxes in relation to landscape scale processes: linking process understanding to regional scale carbon mass-balances

NASA Astrophysics Data System (ADS)

Van Oost, Kristof; Nadeu, Elisabet; Wiaux, François; Wang, Zhengang; Stevens, François; Vanclooster, Marnik; Tran, Anh; Bogaert, Patrick; Doetterl, Sebastian; Lambot, Sébastien; Van wesemael, Bas

2014-05-01

In this paper, we synthesize the main outcomes of a collaborative project (2009-2014) initiated at the UCL (Belgium). The main objective of the project was to increase our understanding of soil organic matter dynamics in complex landscapes and use this to improve predictions of regional scale soil carbon balances. In a first phase, the project characterized the emergent spatial variability in soil organic matter storage and key soil properties at the regional scale. Based on the integration of remote sensing, geomorphological and soil analysis techniques, we quantified the temporal and spatial variability of soil carbon stock and pool distribution at the local and regional scales. This work showed a linkage between lateral fluxes of C in relation with sediment transport and the spatial variation in carbon storage at multiple spatial scales. In a second phase, the project focused on characterizing key controlling factors and process interactions at the catena scale. In-situ experiments of soil CO2 respiration showed that the soil carbon response at the catena scale was spatially heterogeneous and was mainly controlled by the catenary variation of soil physical attributes (soil moisture, temperature, C quality). The hillslope scale characterization relied on advanced hydrogeophysical techniques such as GPR (Ground Penetrating Radar), EMI (Electromagnetic induction), ERT (Electrical Resistivity Tomography), and geophysical inversion and data mining tools. Finally, we report on the integration of these insights into a coupled and spatially explicit model and its application. Simulations showed that C stocks and redistribution of mass and energy fluxes are closely coupled, they induce structured spatial and temporal patterns with non negligible attached uncertainties. We discuss the main outcomes of these activities in relation to sink-source behavior and relevance of erosion processes for larger-scale C budgets.

Large-scale derived flood frequency analysis based on continuous simulation

NASA Astrophysics Data System (ADS)

Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

There is an increasing need for spatially consistent flood risk assessments at the regional scale (several 100.000 km2), in particular in the insurance industry and for national risk reduction strategies. However, most large-scale flood risk assessments are composed of smaller-scale assessments and show spatial inconsistencies. To overcome this deficit, a large-scale flood model composed of a weather generator and catchments models was developed reflecting the spatially inherent heterogeneity. The weather generator is a multisite and multivariate stochastic model capable of generating synthetic meteorological fields (precipitation, temperature, etc.) at daily resolution for the regional scale. These fields respect the observed autocorrelation, spatial correlation and co-variance between the variables. They are used as input into catchment models. A long-term simulation of this combined system enables to derive very long discharge series at many catchment locations serving as a basic for spatially consistent flood risk estimates at the regional scale. This combined model was set up and validated for major river catchments in Germany. The weather generator was trained by 53-year observation data at 528 stations covering not only the complete Germany but also parts of France, Switzerland, Czech Republic and Australia with the aggregated spatial scale of 443,931 km2. 10.000 years of daily meteorological fields for the study area were generated. Likewise, rainfall-runoff simulations with SWIM were performed for the entire Elbe, Rhine, Weser, Donau and Ems catchments. The validation results illustrate a good performance of the combined system, as the simulated flood magnitudes and frequencies agree well with the observed flood data. Based on continuous simulation this model chain is then used to estimate flood quantiles for the whole Germany including upstream headwater catchments in neighbouring countries. This continuous large scale approach overcomes the several drawbacks reported in traditional approaches for the derived flood frequency analysis and therefore is recommended for large scale flood risk case studies.

Individual contributions of climate and vegetation change to soil moisture trends across multiple spatial scales.

PubMed

Feng, Huihui

2016-09-07

Climate and vegetation change are two dominating factors for soil moisture trend. However, their individual contributions remain unknown due to their complex interaction. Here, I separated their contributions through a trajectory-based method across the global, regional and local scales. Our results demonstrated that climate change accounted for 98.78% and 114.64% of the global drying and wetting trend. Vegetation change exhibited a relatively weak influence (contributing 1.22% and -14.64% of the global drying and wetting) because it occurred in a limited area on land. Regionally, the impact of vegetation change cannot be neglected, which contributed -40.21% of the soil moisture change in the wetting zone. Locally, the contributions strongly correlated to the local environmental characteristics. Vegetation negatively affected soil moisture trends in the dry and sparsely vegetated regions and positively in the wet and densely vegetated regions. I conclude that individual contributions of climate and vegetation change vary at the global, regional and local scales. Climate change dominates the soil moisture trends, while vegetation change acts as a regulator to drying or wetting the soil under the changing climate.

Large-scale model of flow in heterogeneous and hierarchical porous media

NASA Astrophysics Data System (ADS)

Chabanon, Morgan; Valdés-Parada, Francisco J.; Ochoa-Tapia, J. Alberto; Goyeau, Benoît

2017-11-01

Heterogeneous porous structures are very often encountered in natural environments, bioremediation processes among many others. Reliable models for momentum transport are crucial whenever mass transport or convective heat occurs in these systems. In this work, we derive a large-scale average model for incompressible single-phase flow in heterogeneous and hierarchical soil porous media composed of two distinct porous regions embedding a solid impermeable structure. The model, based on the local mechanical equilibrium assumption between the porous regions, results in a unique momentum transport equation where the global effective permeability naturally depends on the permeabilities at the intermediate mesoscopic scales and therefore includes the complex hierarchical structure of the soil. The associated closure problem is numerically solved for various configurations and properties of the heterogeneous medium. The results clearly show that the effective permeability increases with the volume fraction of the most permeable porous region. It is also shown that the effective permeability is sensitive to the dimensionality spatial arrangement of the porous regions and in particular depends on the contact between the impermeable solid and the two porous regions.

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

Wolfram, Phillip J.; Ringler, Todd D.; Maltrud, Mathew E.

Isopycnal diffusivity due to stirring by mesoscale eddies in an idealized, wind-forced, eddying, midlatitude ocean basin is computed using Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT). Simulation is performed via LIGHT within the Model for Prediction across Scales Ocean (MPAS-O). Simulations are performed at 4-, 8-, 16-, and 32-km resolution, where the first Rossby radius of deformation (RRD) is approximately 30 km. Scalar and tensor diffusivities are estimated at each resolution based on 30 ensemble members using particle cluster statistics. Each ensemble member is composed of 303 665 particles distributed across five potential density surfaces. Diffusivity dependence upon modelmore » resolution, velocity spatial scale, and buoyancy surface is quantified and compared with mixing length theory. The spatial structure of diffusivity ranges over approximately two orders of magnitude with values of O(10 5) m 2 s –1 in the region of western boundary current separation to O(10 3) m 2 s –1 in the eastern region of the basin. Dominant mixing occurs at scales twice the size of the first RRD. Model resolution at scales finer than the RRD is necessary to obtain sufficient model fidelity at scales between one and four RRD to accurately represent mixing. Mixing length scaling with eddy kinetic energy and the Lagrangian time scale yield mixing efficiencies that typically range between 0.4 and 0.8. In conclusion, a reduced mixing length in the eastern region of the domain relative to the west suggests there are different mixing regimes outside the baroclinic jet region.« less

Structure Function Scaling Exponent and Intermittency in the Wake of a Wind Turbine Array

NASA Astrophysics Data System (ADS)

Aseyev, Aleksandr; Ali, Naseem; Cal, Raul

2015-11-01

Hot-wire measurements obtained in a 3 × 3 wind turbine array boundary layer are utilized to analyze high order structure functions, intermittency effects as well as the probability density functions of velocity increments at different scales within the energy cascade. The intermittency exponent is found to be greater in the far wake region in comparison to the near wake. At hub height, the intermittency exponent is found to be null. ESS scaling exponents of the second, fourth, and fifth order structure functions remain relatively constant as a function of height in the far-wake whereas in the near-wake these highly affected by the passage of the rotor thus showing a dependence on physical location. When comparing with proposed models, these generally over predict the structure functions in the far wake region. The pdf distributions in the far wake region display wider tails compared to the near wake region, and constant skewness hypothesis based on the local isotropy is verified in the wake. CBET-1034581.

Linking Local Scale Ecosystem Science to Regional Scale Management

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J.; Peiffer, S.

2012-04-01

Ecosystem management with respect to sufficient water yield, a quality water supply, habitat and biodiversity conservation, and climate change effects requires substantial observational data at a range of scales. Complex interactions of local physical processes oftentimes vary over space and time, particularly in locations with extreme meteorological conditions. Modifications to local conditions (ie: agricultural land use changes, nutrient additions, landscape management, water usage) can further affect regional ecosystem services. The international, inter-disciplinary TERRECO research group is intensively investigating a variety of local processes, parameters, and conditions to link complex physical, economic, and social interactions at the regional scale. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. The data are used to parameterize suite of models describing local to landscape level water, sediment, nutrient, and monetary relationships. We focus on using the agricultural and hydrological SWAT model to synthesize the experimental field data and local-scale models throughout the catchment. The approach of our study was to describe local scientific processes, link potential interrelationships between different processes, and predict environmentally efficient management efforts. The Haean catchment case study shows how research can be structured to provide cross-disciplinary scientific linkages describing complex ecosystems and landscapes that can be used for regional management evaluations and predictions.

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

NASA Astrophysics Data System (ADS)

di Luca, Alejandro; de Elía, Ramón; Laprise, René

2012-03-01

Regional Climate Models (RCMs) constitute the most often used method to perform affordable high-resolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions.

Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio River Basin Summer 2002 storm event.

PubMed

Knebl, M R; Yang, Z-L; Hutchison, K; Maidment, D R

2005-06-01

This paper develops a framework for regional scale flood modeling that integrates NEXRAD Level III rainfall, GIS, and a hydrological model (HEC-HMS/RAS). The San Antonio River Basin (about 4000 square miles, 10,000 km2) in Central Texas, USA, is the domain of the study because it is a region subject to frequent occurrences of severe flash flooding. A major flood in the summer of 2002 is chosen as a case to examine the modeling framework. The model consists of a rainfall-runoff model (HEC-HMS) that converts precipitation excess to overland flow and channel runoff, as well as a hydraulic model (HEC-RAS) that models unsteady state flow through the river channel network based on the HEC-HMS-derived hydrographs. HEC-HMS is run on a 4 x 4 km grid in the domain, a resolution consistent with the resolution of NEXRAD rainfall taken from the local river authority. Watershed parameters are calibrated manually to produce a good simulation of discharge at 12 subbasins. With the calibrated discharge, HEC-RAS is capable of producing floodplain polygons that are comparable to the satellite imagery. The modeling framework presented in this study incorporates a portion of the recently developed GIS tool named Map to Map that has been created on a local scale and extends it to a regional scale. The results of this research will benefit future modeling efforts by providing a tool for hydrological forecasts of flooding on a regional scale. While designed for the San Antonio River Basin, this regional scale model may be used as a prototype for model applications in other areas of the country.

Imaging lithosphere structures using long period surface waves from ambient noise: a case study in western USA

NASA Astrophysics Data System (ADS)

Yang, Y.

2013-12-01

Since the emerging of ambient noise tomography in 2005, it has become a well-established method and been applied all over the world to imaging crustal and uppermost mantle structures because of its exclusive capability to extract short period surface waves. Most studies of ambient noise tomography performed so far use surface waves at periods shorter than 40/50 sec. There are a few studies of long period surface wave tomography from ambient noise (longer than 50 sec) in continental and global scales. To our knowledge, almost no tomography studies have been performed using long period surface waves (~50-200 sec) from ambient noise in regional scales with an aperture of several hundred kilometres. In this study, we demonstrate the capability of using long period surface waves from ambient noise in regional surface wave tomography by showing a case study of western USA using the USArray Transportable component (TA). We select about 150 TA stations located in a region including northern California, northern Nevada and Oregon as the 'base' stations and about 200 stations from Global Seismographic Network (GSN) and The International Federation of Digital Seismograph Networks (FDSN) as the 'remote' stations. We perform monthly cross-correlations of continuous ambient noise data recorded in 2006-2008 between the 'base' stations and the 'remote' stations and then use a stacking method based on instantaneous phase coherence to stack the monthly cross-correlations to obtain the final cross-correlations. The results show that high signal-to-noise ratio long period Raleigh waves are obtained between the 'base' stations and 'remote' stations located several thousand or even more than ten thousand kilometres away from the 'base' stations. By treating each of the 'remote' station as a 'virtual' teleseismic earthquake and measuring surface wave phases at the 'base' stations, we generate phase velocity maps at 50-200 sec periods in the regions covered by the 'base' stations using an array-based two-plane-wave tomography method. To evaluate the reliability of the resulting phase velocity maps, we compare them with published phase velocity maps using the same tomography method but based on teleseismic data. The comparison shows that long period surface wave phase velocity maps based 'virtual' events from ambient noise and those based on natural earthquakes are very similar with differences within the range of uncertainties. The similarity of phase velocity maps justifies the application of long period surface waves from ambient noise in regional lithosphere imaging. The successful extraction of long period surface waves between station pairs with distances as long as several thousand or ten thousand kilometres can link seismic arrays located in different continents, such as CEArray in China and USArray in USA. With the rapid developments of large scale seismic arrays in different continents, those inter-continental surface waves from ambient noise can be incorporated in both regional- and global-scale surface wave tomography to significantly increase the path coverage in both lateral and azimuthal senses, which is essential to improving imaging of high resolution heterogeneities and azimuthal anisotropy, especially at regions with gaps of azimuthal distributions of earthquakes.

Coupling transfer function and GIS for assessing non-point-source groundwater vulnerability at regional scale

NASA Astrophysics Data System (ADS)

Coppola, A.; Comegna, V.; de Simone, L.

2009-04-01

Non-point source (NPS) pollution in the vadose zone is a global environmental problem. The knowledge and information required to address the problem of NPS pollutants in the vadose zone cross several technological and sub disciplinary lines: spatial statistics, geographic information systems (GIS), hydrology, soil science, and remote sensing. The main issues encountered by NPS groundwater vulnerability assessment, as discussed by Stewart [2001], are the large spatial scales, the complex processes that govern fluid flow and solute transport in the unsaturated zone, the absence of unsaturated zone measurements of diffuse pesticide concentrations in 3-D regional-scale space as these are difficult, time consuming, and prohibitively costly, and the computational effort required for solving the nonlinear equations for physically-based modeling of regional scale, heterogeneous applications. As an alternative solution, here is presented an approach that is based on coupling of transfer function and GIS modeling that: a) is capable of solute concentration estimation at a depth of interest within a known error confidence class; b) uses available soil survey, climatic, and irrigation information, and requires minimal computational cost for application; c) can dynamically support decision making through thematic mapping and 3D scenarios This result was pursued through 1) the design and building of a spatial database containing environmental and physical information regarding the study area, 2) the development of the transfer function procedure for layered soils, 3) the final representation of results through digital mapping and 3D visualization. One side GIS modeled environmental data in order to characterize, at regional scale, soil profile texture and depth, land use, climatic data, water table depth, potential evapotranspiration; on the other side such information was implemented in the up-scaling procedure of the Jury's TFM resulting in a set of texture based travel time probability density functions for layered soils each describing a characteristic leaching behavior for soil profiles with similar hydraulic properties. Such behavior, in terms of solute travel time to water table, was then imported back into GIS and finally estimation groundwater vulnerability for each soil unit was represented into a map as well as visualized in 3D.

Scaling up from field to region for wind erosion prediction using a field-scale wind erosion model and GIS

USGS Publications Warehouse

Zobeck, T.M.; Parker, N.C.; Haskell, S.; Guoding, K.

2000-01-01

Factors that affect wind erosion such as surface vegetative and other cover, soil properties and surface roughness usually change spatially and temporally at the field-scale to produce important field-scale variations in wind erosion. Accurate estimation of wind erosion when scaling up from fields to regions, while maintaining meaningful field-scale process details, remains a challenge. The objectives of this study were to evaluate the feasibility of using a field-scale wind erosion model with a geographic information system (GIS) to scale up to regional levels and to quantify the differences in wind erosion estimates produced by different scales of soil mapping used as a data layer in the model. A GIS was used in combination with the revised wind erosion equation (RWEQ), a field-scale wind erosion model, to estimate wind erosion for two 50 km2 areas. Landsat Thematic Mapper satellite imagery from 1993 with 30 m resolution was used as a base map. The GIS database layers included land use, soils, and other features such as roads. The major land use was agricultural fields. Data on 1993 crop management for selected fields of each crop type were collected from local government agency offices and used to 'train' the computer to classify land areas by crop and type of irrigation (agroecosystem) using commercially available software. The land area of the agricultural land uses was overestimated by 6.5% in one region (Lubbock County, TX, USA) and underestimated by about 21% in an adjacent region (Terry County, TX, USA). The total estimated wind erosion potential for Terry County was about four times that estimated for adjacent Lubbock County. The difference in potential erosion among the counties was attributed to regional differences in surface soil texture. In a comparison of different soil map scales in Terry County, the generalised soil map had over 20% more of the land area and over 15% greater erosion potential in loamy sand soils than did the detailed soil map. As a result, the wind erosion potential determined using the generalised soil map Was about 26% greater than the erosion potential estimated by using the detailed soil map in Terry County. This study demonstrates the feasibility of scaling up from fields to regions to estimate wind erosion potential by coupling a field-scale wind erosion model with GIS and identifies possible sources of error with this approach.

Sustainable Land Management's potential for climate change adaptation in Mediterranean environments: a regional scale assessment

NASA Astrophysics Data System (ADS)

Eekhout, Joris P. C.; de Vente, Joris

2017-04-01

Climate change has strong implications for many essential ecosystem services, such as provision of drinking and irrigation water, soil erosion and flood control. Especially large impacts are expected in the Mediterranean, already characterised by frequent floods and droughts. The projected higher frequency of extreme weather events under climate change will lead to an increase of plant water stress, reservoir inflow and sediment yield. Sustainable Land Management (SLM) practices are increasingly promoted as climate change adaptation strategy and to increase resilience against extreme events. However, there is surprisingly little known about their impacts and trade-offs on ecosystem services at regional scales. The aim of this research is to provide insight in the potential of SLM for climate change adaptation, focusing on catchment-scale impacts on soil and water resources. We applied a spatially distributed hydrological model (SPHY), coupled with an erosion model (MUSLE) to the Segura River catchment (15,978 km2) in SE Spain. We run the model for three periods: one reference (1981-2000) and two future scenarios (2031-2050 and 2081-2100). Climate input data for the future scenarios were based on output from 9 Regional Climate Models and for different emission scenarios (RCP 4.5 and RCP 8.5). Realistic scenarios of SLM practices were developed based on a local stakeholder consultation process. The evaluated SLM scenarios focussed on reduced tillage and organic amendments under tree and cereal crops, covering 24% and 15% of the catchment, respectively. In the reference scenario, implementation of SLM at the field-scale led to an increase of the infiltration capacity of the soil and a reduction of surface runoff up to 29%, eventually reducing catchment-scale reservoir inflow by 6%. This led to a reduction of field-scale sediment yield of more than 50% and a reduced catchment-scale sediment flux to reservoirs of 5%. SLM was able to fully mitigate the effect of climate change at the field-scale and partly at the catchment-scale. Therefore, we conclude that large-scale adoption of SLM can effectively contribute to climate change adaptation by increasing the soil infiltration capacity, the soil water retention capacity and soil moisture content in the rootzone, leading to less crop stress. These findings of regional scale impacts of SLM are of high relevance for land-owners, -managers and policy makers to design effective climate change adaptation strategies.

Blood vessel segmentation in color fundus images based on regional and Hessian features.

PubMed

Shah, Syed Ayaz Ali; Tang, Tong Boon; Faye, Ibrahima; Laude, Augustinus

2017-08-01

To propose a new algorithm of blood vessel segmentation based on regional and Hessian features for image analysis in retinal abnormality diagnosis. Firstly, color fundus images from the publicly available database DRIVE were converted from RGB to grayscale. To enhance the contrast of the dark objects (blood vessels) against the background, the dot product of the grayscale image with itself was generated. To rectify the variation in contrast, we used a 5 × 5 window filter on each pixel. Based on 5 regional features, 1 intensity feature and 2 Hessian features per scale using 9 scales, we extracted a total of 24 features. A linear minimum squared error (LMSE) classifier was trained to classify each pixel into a vessel or non-vessel pixel. The DRIVE dataset provided 20 training and 20 test color fundus images. The proposed algorithm achieves a sensitivity of 72.05% with 94.79% accuracy. Our proposed algorithm achieved higher accuracy (0.9206) at the peripapillary region, where the ocular manifestations in the microvasculature due to glaucoma, central retinal vein occlusion, etc. are most obvious. This supports the proposed algorithm as a strong candidate for automated vessel segmentation.

Are Regional Habitat Models Useful at a Local-Scale? A Case Study of Threatened and Common Insectivorous Bats in South-Eastern Australia

PubMed Central

McConville, Anna; Law, Bradley S.; Mahony, Michael J.

2013-01-01

Habitat modelling and predictive mapping are important tools for conservation planning, particularly for lesser known species such as many insectivorous bats. However, the scale at which modelling is undertaken can affect the predictive accuracy and restrict the use of the model at different scales. We assessed the validity of existing regional-scale habitat models at a local-scale and contrasted the habitat use of two morphologically similar species with differing conservation status (Mormopterus norfolkensis and Mormopterus species 2). We used negative binomial generalised linear models created from indices of activity and environmental variables collected from systematic acoustic surveys. We found that habitat type (based on vegetation community) best explained activity of both species, which were more active in floodplain areas, with most foraging activity recorded in the freshwater wetland habitat type. The threatened M. norfolkensis avoided urban areas, which contrasts with M. species 2 which occurred frequently in urban bushland. We found that the broad habitat types predicted from local-scale models were generally consistent with those from regional-scale models. However, threshold-dependent accuracy measures indicated a poor fit and we advise caution be applied when using the regional models at a fine scale, particularly when the consequences of false negatives or positives are severe. Additionally, our study illustrates that habitat type classifications can be important predictors and we suggest they are more practical for conservation than complex combinations of raw variables, as they are easily communicated to land managers. PMID:23977296

[Relationships of forest fire with lightning in Daxing' anling Mountains, Northeast China].

PubMed

Lei, Xiao-Li; Zhou, Guang-Sheng; Jia, Bing-Rui; Li, Shuai

2012-07-01

Forest fire is an important factor affecting forest ecosystem succession. Recently, forest fire, especially forest lightning fire, shows an increasing trend under global warming. To study the relationships of forest fire with lightning is essential to accurately predict the forest fire in time. Daxing' anling Mountains is a region with high frequency of forest lightning fire in China, and an important experiment site to study the relationships of forest fire with lightning. Based on the forest fire records and the corresponding lightning and meteorological observation data in the Mountains from 1966 to 2007, this paper analyzed the relationships of forest fire with lightning in this region. In the period of 1966-2007, both the lightning fire number and the fired forest area in this region increased significantly. The meteorological factors affecting the forest lighting fire were related to temporal scales. At yearly scale, the forest lightning fire was significantly correlated with precipitation, with a correlation coefficient of -0.489; at monthly scale, it had a significant correlation with air temperature, the correlation coefficient being 0.18. The relationship of the forest lightning fire with lightning was also related to temporal scales. At yearly scale, there was no significant correlation between them; at monthly scale, the forest lightning fire was strongly correlated with lightning and affected by precipitation; at daily scale, a positive correlation was observed between forest lightning fire and lightning when the precipitation was less than 5 mm. According to these findings, a fire danger index based on ADTD lightning detection data was established, and a forest lightning fire forecast model was developed. The prediction accuracy of this model for the forest lightning fire in Daxing' anling Mountains in 2005-2007 was > 80%.

Design of a reliable and operational landslide early warning system at regional scale

NASA Astrophysics Data System (ADS)

Calvello, Michele; Piciullo, Luca; Gariano, Stefano Luigi; Melillo, Massimo; Brunetti, Maria Teresa; Peruccacci, Silvia; Guzzetti, Fausto

2017-04-01

Landslide early warning systems at regional scale are used to warn authorities, civil protection personnel and the population about the occurrence of rainfall-induced landslides over wide areas, typically through the prediction and measurement of meteorological variables. A warning model for these systems must include a regional correlation law and a decision algorithm. A regional correlation law can be defined as a functional relationship between rainfall and landslides; it is typically based on thresholds of rainfall indicators (e.g., cumulated rainfall, rainfall duration) related to different exceedance probabilities of landslide occurrence. A decision algorithm can be defined as a set of assumptions and procedures linking rainfall thresholds to warning levels. The design and the employment of an operational and reliable early warning system for rainfall-induced landslides at regional scale depend on the identification of a reliable correlation law as well as on the definition of a suitable decision algorithm. Herein, a five-step process chain addressing both issues and based on rainfall thresholds is proposed; the procedure is tested in a landslide-prone area of the Campania region in southern Italy. To this purpose, a database of 96 shallow landslides triggered by rainfall in the period 2003-2010 and rainfall data gathered from 58 rain gauges are used. First, a set of rainfall thresholds are defined applying a frequentist method to reconstructed rainfall conditions triggering landslides in the test area. In the second step, several thresholds at different exceedance probabilities are evaluated, and different percentile combinations are selected for the activation of three warning levels. Subsequently, within steps three and four, the issuing of warning levels is based on the comparison, over time and for each combination, between the measured rainfall and the pre-defined warning level thresholds. Finally, the optimal percentile combination to be employed in the regional early warning system is selected evaluating the model performance in terms of success and error indicators by means of the "event, duration matrix, performance" (EDuMaP) method.

Evaluation for relationship among source parameters of underground nuclear tests in Northern Korean Peninsula

NASA Astrophysics Data System (ADS)

Kim, G.; Che, I. Y.

2017-12-01

We evaluated relationship among source parameters of underground nuclear tests in northern Korean Peninsula using regional seismic data. Dense global and regional seismic networks are incorporated to measure locations and origin times precisely. Location analyses show that distance among the locations is tiny on a regional scale. The tiny location-differences validate a linear model assumption. We estimated source spectral ratios by excluding path effects based spectral ratios of the observed seismograms. We estimated empirical relationship among depth of burials and yields based on theoretical source models.

Projected changes to precipitation extremes over the Canadian Prairies using multi-RCM ensemble

NASA Astrophysics Data System (ADS)

Masud, M. B.; Khaliq, M. N.; Wheater, H. S.

2016-12-01

Information on projected changes to precipitation extremes is needed for future planning of urban drainage infrastructure and storm water management systems and to sustain socio-economic activities and ecosystems at local, regional and other scales of interest. This study explores the projected changes to seasonal (April-October) precipitation extremes at daily, hourly and sub-hourly scales over the Canadian Prairie Provinces of Alberta, Saskatchewan, and Manitoba, based on the North American Regional Climate Change Assessment Program multi-Regional Climate Model (RCM) ensemble and regional frequency analysis. The performance of each RCM is evaluated regarding boundary and performance errors to study various sources of uncertainties and the impact of large-scale driving fields. In the absence of RCM-simulated short-duration extremes, a framework is developed to derive changes to extremes of these durations. Results from this research reveal that the relative changes in sub-hourly extremes are higher than those in the hourly and daily extremes. Overall, projected changes in precipitation extremes are larger for southeastern parts of this region than southern and northern areas, and smaller for southwestern and western parts of the study area. Keywords: climate change, precipitation extremes, regional frequency analysis, NARCCAP, Canadian Prairie provinces

Spatially Resolved Distribution of Fe Species around Microbes at the Submicron Scale in Natural Bacteriogenic Iron Oxides.

PubMed

Suga, Hiroki; Kikuchi, Sakiko; Takeichi, Yasuo; Miyamoto, Chihiro; Miyahara, Masaaki; Mitsunobu, Satoshi; Ohigashi, Takuji; Mase, Kazuhiko; Ono, Kanta; Takahashi, Yoshio

2017-09-27

Natural bacteriogenic iron oxides (BIOS) were investigated using local-analyzable synchrotron-based scanning transmission X-ray microscopy (STXM) with a submicron-scale resolution. Cell, cell sheath interface (EPS), and sheath in the BIOS were clearly depicted using C-, N-, and O- near edge X-ray absorption fine structure (NEXAFS) obtained through STXM measurements. Fe-NEXAFS obtained from different regions of BIOS indicated that the most dominant iron mineral species was ferrihydrite. Fe(II)- and/or Fe(III)-acidic polysaccharides accompanied ferrihydrite near the cell and EPS regions. Our STXM/NEXAFS analysis showed that Fe species change continuously between the cell, EPS, and sheath under several 10-nm scales.

REGIONAL OXIDANT MODEL (ROM) USER'S GUIDE, PART 3: THE CORE MODEL

EPA Science Inventory

The Regional Oxidant Model (ROM) determines hourly concentrations and fates of zone and 34 other chemical species over a scale of 1000 km x 1000 km for ozone "episodes" of up to one month's duration. he model structure, based on phenomenological concepts, consists of 3 1/2 layers...

REGIONAL OXIDANT MODEL (ROM) USER'S GUIDE, PART 1: THE ROM PREPROCESSORS

EPA Science Inventory

The Regional Oxidant Model (ROM) determines hourly concentrations and fates of zone and 34 other chemical species over a scale of 1000 km x 1000 km for ozone "episodes" of up to one month's duration. he model structure, based on phenomenological concepts, consists of 3 1/2 layers...

GMLC Hawaii Regional Partnership: Distributed Inverter-Based Grid Frequency Support

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

Nelson, Austin; Hoke, Andy

This presentation is part of a panel session at the IEEE ISGT conference on Grid Modernization Initiative projects. This segment of the panel session provides a brief overview of a Hawaii Regional Partnership project focusing grid frequency support from distributed resources on the fastest time scales.

Regional Climate Simulation with a Variable Resolution Stretched Grid GCM: The Regional Down-Scaling Effects

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Suarez, Max; Sawyer, William; Govindaraju, Ravi C.

1999-01-01

The results obtained with the variable resolution stretched grid (SG) GEOS GCM (Goddard Earth Observing System General Circulation Models) are discussed, with the emphasis on the regional down-scaling effects and their dependence on the stretched grid design and parameters. A variable resolution SG-GCM and SG-DAS using a global stretched grid with fine resolution over an area of interest, is a viable new approach to REGIONAL and subregional CLIMATE studies and applications. The stretched grid approach is an ideal tool for representing regional to global scale interactions. It is an alternative to the widely used nested grid approach introduced a decade ago as a pioneering step in regional climate modeling. The GEOS SG-GCM is used for simulations of the anomalous U.S. climate events of 1988 drought and 1993 flood, with enhanced regional resolution. The height low level jet, precipitation and other diagnostic patterns are successfully simulated and show the efficient down-scaling over the area of interest the U.S. An imitation of the nested grid approach is performed using the developed SG-DAS (Data Assimilation System) that incorporates the SG-GCM. The SG-DAS is run with withholding data over the area of interest. The design immitates the nested grid framework with boundary conditions provided from analyses. No boundary condition buffer is needed for the case due to the global domain of integration used for the SG-GCM and SG-DAS. The experiments based on the newly developed versions of the GEOS SG-GCM and SG-DAS, with finer 0.5 degree (and higher) regional resolution, are briefly discussed. The major aspects of parallelization of the SG-GCM code are outlined. The KEY OBJECTIVES of the study are: 1) obtaining an efficient DOWN-SCALING over the area of interest with fine and very fine resolution; 2) providing CONSISTENT interactions between regional and global scales including the consistent representation of regional ENERGY and WATER BALANCES; 3) providing a high computational efficiency for future SG-GCM and SG-DAS versions using PARALLEL codes.

Characterizing and modelling river channel migration rates at a regional scale: Case study of south-east France.

PubMed

Alber, Adrien; Piégay, Hervé

2017-11-01

An increased awareness by river managers of the importance of river channel migration to sediment dynamics, habitat complexity and other ecosystem functions has led to an advance in the science and practice of identifying, protecting or restoring specific erodible corridors across which rivers are free to migrate. One current challenge is the application of these watershed-specific goals at the regional planning scales (e.g., the European Water Framework Directive). This study provides a GIS-based spatial analysis of the channel migration rates at the regional-scale. As a case study, 99 reaches were sampled in the French part of the Rhône Basin and nearby tributaries of the Mediterranean Sea (111,300 km 2 ). We explored the spatial correlation between the channel migration rate and a set of simple variables (e.g., watershed area, channel slope, stream power, active channel width). We found that the spatial variability of the channel migration rates was primary explained by the gross stream power (R 2  = 0.48) and more surprisingly by the active channel width scaled by the watershed area. The relationship between the absolute migration rate and the gross stream power is generally consistent with the published empirical models for freely meandering rivers, whereas it is less significant for the multi-thread reaches. The discussion focused on methodological constraints for a regional-scale modelling of the migration rates, and the interpretation of the empirical models. We hypothesize that the active channel width scaled by the watershed area is a surrogate for the sediment supply which may be a more critical factor than the bank resistance for explaining the regional-scale variability of the migration rates. Copyright © 2016 Elsevier Ltd. All rights reserved.

Geologic Map of the Thaumasia Region, Mars

USGS Publications Warehouse

Dohm, Janes M.; Tanaka, Kenneth L.; Hare, Trent M.

2001-01-01

The geology of the Thaumasia region (fig. 1, sheet 3) includes a wide array of rock materials, depositional and erosional landforms, and tectonic structures. The region is dominated by the Thaumasia plateau, which includes central high lava plains ringed by highly deformed highlands; the plateau may comprise the ancestral center of Tharsis tectonism (Frey, 1979; Plescia and Saunders, 1982). The extensive structural deformation of the map region, which is without parallel on Mars in both complexity and diversity, occurred largely throughout the Noachian and Hesperian periods (Tanaka and Davis, 1988; Scott and Dohm, 1990a). The deformation produced small and large extensional and contractional structures (fig. 2, sheet 3) that resulted from stresses related to the formation of Tharsis (Frey, 1979; Wise and others, 1979; Plescia and Saunders, 1982; Banerdt and others, 1982, 1992; Watters and Maxwell, 1986; Tanaka and Davis, 1988; Francis, 1988; Watters, 1993; Schultz and Tanaka, 1994), from magmatic-driven uplifts, such as at Syria Planum (Tanaka and Davis, 1988; Dohm and others, 1998; Dohm and Tanaka, 1999) and central Valles Marineris (Dohm and others, 1998, Dohm and Tanaka, 1999), and from the Argyre impact (Wilhelms, 1973; Scott and Tanaka, 1986). In addition, volcanic, eolian, and fluvial processes have highly modified older surfaces in the map region. Local volcanic and tectonic activity often accompanied episodes of valley formation. Our mapping depicts and describes the diverse terrains and complex geologic history of this unique ancient tectonic region of Mars. The geologic (sheet 1), paleotectonic (sheet 2), and paleoerosional (sheet 3) maps of the Thaumasia region were compiled on a Viking 1:5,000,000-scale digital photomosaic base. The base is a combination of four quadrangles: the southeast part of Phoenicis Lacus (MC–17), most of the southern half of Coprates (MC–18), a large part of Thaumasia (MC–25), and the northwest margin of Argyre (MC–26). The medium-resolution Viking images used for mapping and base preparation also formed the basis of the 1:2,000,000 scale subquadrangle series. Earlier geologic maps of all or parts of the region include: (1) maps of the Phoenicis Lacus, Coprates, Thaumasia, and Argyre quadrangles at 1:5,000,000 scale based mainly on Mariner 9 images (respectively, Masursky and others, 1978; McCauley, 1978; McGill, 1978; and Hodges, 1980), (2) the global map of Mars at 1:25,000,000 (Scott and Carr, 1978) compiled largely from the 1:5,000,000 scale geologic maps, (3) maps showing lava flows in the Tharsis region at 1:2,000,000 scale compiled from Viking and Mariner 9 images (Scott, 1981; Scott and Tanaka, 1981a, b; Scott and others, 1981), (4) the map of the western equatorial region of Mars at 1:15,000,000 scale based on Viking images (Scott and Tanaka, 1986), and (5) the map of the Valles Marineris region at 1:2,000,000 scale compiled from Viking images (Witbeck and others, 1991). The previous maps have described the overall geology and geomorphology of the region but have not unraveled the detailed stratigraphy and complex evolution of this unique and geologically diverse martian province. The main purpose of this comprehensive mapping project is to reconstruct the stratigraphic, structural, and erosional histories of the Thaumasia region. The region is the last major province of the Tharsis region to undergo detailed structural mapping using Viking images; its history is essential to documenting the overall tectonic history of Tharsis. Other provinces of Tharsis that have been structurally mapped include Syria Planum (Tanaka and Davis, 1988), Tempe Terra and Ulysses Patera (Scott and Dohm, 1990b), and Alba Patera (Tanaka, 1990). Another primary mapping objective is to determine the region's volcanic history and assess the relations among fault systems and volcanoes (Wise and others, 1979; Scott and Tanaka, 1980; Whitford-Stark, 1982; Scott and Dohm, 1990a). A secondary mapping objective is to determine the distribution and ages of valleys. In our study, we incorporated detailed photogeologic mapping, comprehensive crater statistics (table 1), and geologic, paleotectonic, and paleoerosional Geographic Information System (GIS) databases. Sheets 1–3 show geologic units, faults and other significant structures, and valleys, respectively. To help unravel the complex geologic history of the Thaumasia region, we transferred the highly detailed geologic unit, paleotectonic, and paleoerosional information of sheets 1–3 into a multilayered GIS database for comparative analysis. The geologic information was transferred from hard copy into a digital format by scanning at 25 micron resolution on a drum scanner. The 2-bit scanned image was then converted to an x,y coordinate system using ARC/INFO's vectorization routine. The geologic unit, structural, and erosional data were transformed into the original map projection, Lambert Conformal. The average transformation root mean square error was 0.25 km (acceptable for the Thaumasia map base at 1:5,000,000 scale). After transformation, the features were properly attributed and tediously checked. Once digitized, the map data can be transformed into any map projection depending on the type of data analysis. For example, the equal-area sinusoidal projection was used for determining the precise area of geologic units (table 1). In addition to the geologic map and its attendant stratigraphic section, correlation chart, and description of map units, we include text sections that clarify the histories and temporal, spatial, and causal relations of the various geologic units and landforms of the Thaumasia region. The geologic summary section defines the sequence of major geologic events.

Central Atlantic regional ecological test site

NASA Technical Reports Server (NTRS)

Alexander, R. H.

1972-01-01

The work of the Central Atlantic Regional Ecological Test Site (CARETS) project is discussed. The primary aim of CARETS is to test the hypothesis that data from ERTS-A can be made an integral part of a regional land resources information system, encompassing both inventory of the resource base and monitoring of changes, along with their effects on the quality of the environment. Another objective of the project is to determine scaling factors for developing land use information and regional analysis for regions of any given size.

AgMIP 1.5°C Assessment: Mitigation and Adaptation at Coordinated Global and Regional Scales

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2016-12-01

The AgMIP 1.5°C Coordinated Global and Regional Integrated Assessments of Climate Change and Food Security (AgMIP 1.5 CGRA) is linking site-based crop and livestock models with similar models run on global grids, and then links these biophysical components with economics models and nutrition metrics at regional and global scales. The AgMIP 1.5 CGRA assessment brings together experts in climate, crop, livestock, economics, nutrition, and food security to define the 1.5°C Protocols and guide the process throughout the assessment. Scenarios are designed to consistently combine elements of intertwined storylines of future society including socioeconomic development (Shared Socioeconomic Pathways), greenhouse gas concentrations (Representative Concentration Pathways), and specific pathways of agricultural sector development (Representative Agricultural Pathways). Shared Climate Policy Assumptions will be extended to provide additional agricultural detail on mitigation and adaptation strategies. The multi-model, multi-disciplinary, multi-scale integrated assessment framework is using scenarios of economic development, adaptation, mitigation, food policy, and food security. These coordinated assessments are grounded in the expertise of AgMIP partners around the world, leading to more consistent results and messages for stakeholders, policymakers, and the scientific community. The early inclusion of nutrition and food security experts has helped to ensure that assessment outputs include important metrics upon which investment and policy decisions may be based. The CGRA builds upon existing AgMIP research groups (e.g., the AgMIP Wheat Team and the AgMIP Global Gridded Crop Modeling Initiative; GGCMI) and regional programs (e.g., AgMIP Regional Teams in Sub-Saharan Africa and South Asia), with new protocols for cross-scale and cross-disciplinary linkages to ensure the propagation of expert judgment and consistent assumptions.

In the Shadow of Coal: How Large-Scale Industries Contributed to Present-Day Regional Differences in Personality and Well-Being.

PubMed

Obschonka, Martin; Stuetzer, Michael; Rentfrow, Peter J; Shaw-Taylor, Leigh; Satchell, Max; Silbereisen, Rainer K; Potter, Jeff; Gosling, Samuel D

2017-11-20

Recent research has identified regional variation of personality traits within countries but we know little about the underlying drivers of this variation. We propose that the Industrial Revolution, as a key era in the history of industrialized nations, has led to a persistent clustering of well-being outcomes and personality traits associated with psychological adversity via processes of selective migration and socialization. Analyzing data from England and Wales, we examine relationships between the historical employment share in large-scale coal-based industries (coal mining and steam-powered manufacturing industries that used this coal as fuel for their steam engines) and today's regional variation in personality and well-being. Even after controlling for possible historical confounds (historical energy supply, education, wealth, geology, climate, population density), we find that the historical local dominance of large-scale coal-based industries predicts today's markers of psychological adversity (lower Conscientiousness [and order facet scores], higher Neuroticism [and anxiety and depression facet scores], lower activity [an Extraversion facet], and lower life satisfaction and life expectancy). An instrumental variable analysis, using the historical location of coalfields, supports the causal assumption behind these effects (with the exception of life satisfaction). Further analyses focusing on mechanisms hint at the roles of selective migration and persisting economic hardship. Finally, a robustness check in the U.S. replicates the effect of the historical concentration of large-scale industries on today's levels of psychological adversity. Taken together, the results show how today's regional patterns of personality and well-being (which shape the future trajectories of these regions) may have their roots in major societal changes underway decades or centuries earlier. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Regional hydro-climatic impacts of contemporary Amazonian deforestation

NASA Astrophysics Data System (ADS)

Khanna, Jaya

More than 17% of the Amazon rainforest has been cleared in the past three decades triggering important climatological and societal impacts. This thesis is devoted to identifying and explaining the regional hydroclimatic impacts of this change employing multidecadal satellite observations and numerical simulations providing an integrated perspective on this topic. The climatological nature of this study motivated the implementation and application of a cloud detection technique to a new geostationary satellite dataset. The resulting sub daily, high spatial resolution, multidecadal time series facilitated the detection of trends and variability in deforestation triggered cloud cover changes. The analysis was complemented by satellite precipitation, reanalysis and ground based datasets and attribution with the variable resolution Ocean-Land-Atmosphere-Model. Contemporary Amazonian deforestation affects spatial scales of hundreds of kilometers. But, unlike the well-studied impacts of a few kilometers scale deforestation, the climatic response to contemporary, large scale deforestation is neither well observed nor well understood. Employing satellite datasets, this thesis shows a transition in the regional hydroclimate accompanying increasing scales of deforestation, with downwind deforested regions receiving 25% more and upwind deforested regions receiving 25% less precipitation from the deforested area mean. Simulations robustly reproduce these shifts when forced with increasing deforestation alone, suggesting a negligible role of large-scale decadal climate variability in causing the shifts. Furthermore, deforestation-induced surface roughness variations are found necessary to reproduce the observed spatial patterns in recent times illustrating the strong scale-sensitivity of the climatic response to Amazonian deforestation. This phenomenon, inconsequential during the wet season, is found to substantially affect the regional hydroclimate in the local dry and parts of transition seasons, hence occurring in atmospheric conditions otherwise less conducive to thermal convection. Evidence of this phenomenon is found at two large scale deforested areas considered in this thesis. Hence, the 'dynamical' mechanism, which affects the seasons most important for regional ecology, emerges as an impactful convective triggering mechanism. The phenomenon studied in this thesis provides context for thinking about the climate of a future, more patchily forested Amazonia, by articulating relationships between climate and spatial scales of deforestation.

Estimating Soil Organic Carbon stocks and uncertainties at the regional scale following a legacy sampling strategy - a case study from southern Belgium

NASA Astrophysics Data System (ADS)

Chartin, Caroline; Krüger, Inken; Goidts, Esther; Carnol, Monique; van Wesemael, Bas

2017-04-01

The quantification and the spatialisation of reliable SOC stocks (Mg C ha-1) and total stock (Tg C) baselines and associated uncertainties are fundamental to detect the gains or losses in SOC, and to locate sensitive areas with low SOC levels. Here, we aim to both quantify and spatialize SOC stocks at regional scale (southern Belgium) based on data from one non-design-based nor model-based sampling scheme. To this end, we developed a computation procedure based on Digital Soil Mapping techniques and stochastic simulations (Monte-Carlo) allowing the estimation of multiple (here, 10,000) independent spatialized datasets. The computation of the prediction uncertainty accounts for the errors associated to the both estimations of i) SOC stock at the pixel-related area scale and ii) parameters of the spatial model. Based on these 10,000 individuals, median SOC stocks and 90% prediction intervals were computed for each pixel, as well as total SOC stocks and their 90% prediction intervals for selected sub-areas and for the entire study area. Hence, a Generalised Additive Model (GAM) explaining 69.3 % of the SOC stock variance was calibrated and then validated (R2 = 0.64). The model overestimated low SOC stock (below 50 Mg C ha-1) and underestimated high SOC stock (especially those above 100 Mg C kg-1). A positive gradient of SOC stock occurred from the northwest to the center of Wallonia with a slight decrease on the southernmost part, correlating to the evolution of precipitation and temperature (along with elevation) and dominant land use. At the catchment scale higher SOC stocks were predicted on valley bottoms, especially for poorly drained soils under grassland. Mean predicted SOC stocks for cropland and grassland in Wallonia were of 26.58 Tg C (SD 1.52) and 43.30 Tg C (2.93), respectively. The procedure developed here allowed to predict realistic spatial patterns of SOC stocks all over agricultural lands of southern Belgium and to produce reliable statistics of total SOC stocks for each of the 20 combinations of land use / agricultural regions of Wallonia. This procedure appears useful to produce soil maps as policy tools in conducting sustainable management at regional and national scales, and to compute statistics which comply with specific requirements of reporting activities.

Parameter Uncertainty Analysis Using Monte Carlo Simulations for a Regional-Scale Groundwater Model

NASA Astrophysics Data System (ADS)

Zhang, Y.; Pohlmann, K.

2016-12-01

Regional-scale grid-based groundwater models for flow and transport often contain multiple types of parameters that can intensify the challenge of parameter uncertainty analysis. We propose a Monte Carlo approach to systematically quantify the influence of various types of model parameters on groundwater flux and contaminant travel times. The Monte Carlo simulations were conducted based on the steady-state conversion of the original transient model, which was then combined with the PEST sensitivity analysis tool SENSAN and particle tracking software MODPATH. Results identified hydrogeologic units whose hydraulic conductivity can significantly affect groundwater flux, and thirteen out of 173 model parameters that can cause large variation in travel times for contaminant particles originating from given source zones.

Magnitude scale for the Central American tsunamis

NASA Astrophysics Data System (ADS)

Hatori, Tokutaro

1995-09-01

Based on the tsunami data in the Central American region, the regional characteristic of tsunami magnitude scales is discussed in relation to earthquake magnitudes during the period from 1900 to 1993. Tsunami magnitudes on the Imamura-Iida scale of the 1985 Mexico and 1992 Nicaragua tsunamis are determined to be m=2.5, judging from the tsunami height-distance diagram. The magnitude values of the Central American tsunamis are relatively small compared to earthquakes with similar size in other regions. However, there are a few large tsunamis generated by low-frequency earthquakes such as the 1992 Nicaragua earthquake. Inundation heights of these unusual tsunamis are about 10 times higher than those of normal tsunamis for the same earthquake magnitude ( M s =6.9 7.2). The Central American tsunamis having magnitude m>1 have been observed by the Japanese tide stations, but the effect of directivity toward Japan is very small compared to that of the South American tsunamis.

A state-based national network for effective wildlife conservation

USGS Publications Warehouse

Meretsky, Vicky J.; Maguire, Lynn A.; Davis, Frank W.; Stoms, David M.; Scott, J. Michael; Figg, Dennis; Goble, Dale D.; Griffith, Brad; Henke, Scott E.; Vaughn, Jacqueline; Yaffee, Steven L.

2012-01-01

State wildlife conservation programs provide a strong foundation for biodiversity conservation in the United States, building on state wildlife action plans. However, states may miss the species that are at the most risk at rangewide scales, and threats such as novel diseases and climate change increasingly act at regional and national levels. Regional collaborations among states and their partners have had impressive successes, and several federal programs now incorporate state priorities. However, regional collaborations are uneven across the country, and no national counterpart exists to support efforts at that scale. A national conservation-support program could fill this gap and could work across the conservation community to identify large-scale conservation needs and support efforts to meet them. By providing important information-sharing and capacity-building services, such a program would advance collaborative conservation among the states and their partners, thus increasing both the effectiveness and the efficiency of conservation in the United States.

Using Climate Regionalization to Understand Climate Forecast System Version 2 (CFSv2) Precipitation Performance for the Conterminous United States (CONUS)

NASA Technical Reports Server (NTRS)

Regonda, Satish K.; Zaitchik, Benjamin F.; Badr, Hamada S.; Rodell, Matthew

2016-01-01

Dynamically based seasonal forecasts are prone to systematic spatial biases due to imperfections in the underlying global climate model (GCM). This can result in low-forecast skill when the GCM misplaces teleconnections or fails to resolve geographic barriers, even if the prediction of large-scale dynamics is accurate. To characterize and address this issue, this study applies objective climate regionalization to identify discrepancies between the Climate Forecast SystemVersion 2 (CFSv2) and precipitation observations across the Contiguous United States (CONUS). Regionalization shows that CFSv2 1 month forecasts capture the general spatial character of warm season precipitation variability but that forecast regions systematically differ from observation in some transition zones. CFSv2 predictive skill for these misclassified areas is systematically reduced relative to correctly regionalized areas and CONUS as a whole. In these incorrectly regionalized areas, higher skill can be obtained by using a regional-scale forecast in place of the local grid cell prediction.

COMPARABILITY OF A REGIONAL AND STATE SURVEY: EFFECTS ON FISH IBI ASSESSMENT FOR WEST VIRGINIA, U.S.A.

EPA Science Inventory

The comparability of different survey designs needs to be established to facilitate integration of data across scales and interpretation of trends over time. Probability-based survey designs are now being investigated to allow condition to be assessed at the watershed scale, an...

Geologic Storage at the Basin Scale: Region-Based Basin Modeling, Powder River Basin (PRB), NE Wyoming and SE Montana

NASA Astrophysics Data System (ADS)

Melick, J. J.; Gardner, M. H.

2008-12-01

Carbon capture and storage from the over 2000 power plants is estimated at 3-5 GT/yr, which requires large- scale geologic storage of greenhouse gasses in sedimentary basins. Unfortunately, determination of basin scale storage capacity is currently based on oversimplified geologic models that are difficult to validate. Simplification involves reducing the number of geologic parameters incorporated into the model, modeling with large grid cells, and treatment of subsurface reservoirs as homogeneous media. The latter problem reflects the focus of current models on fluid and/or fluid-rock interactions rather than fluid movement and migration pathways. For example, homogeneous models over emphasize fluid behavior, like the buoyancy of super-critical CO2, and hence overestimate leakage rates. Fluid mixing and fluid-rock interactions cannot be assessed with models that only investigate these reactions at a human time scale. Preliminary and conservative estimates of the total pore volume for the PRB suggest 200 GT of supercritical CO2 can be stored in this typical onshore sedimentary basin. The connected pore volume (CPV) however is not included in this estimate. Geological characterization of the CPV relates subsurface storage units to the most prolific reservoir classes (RCs). The CPV, number of well penetrations, supercritical storage area, and potential leakage pathways characterize each RC. Within each RC, a hierarchy of stratigraphic cycles is populated with stationary sedimentation regions that control rock property distributions by correlating environment of deposition (EOD) to CPV. The degree to which CPV varies between RCs depends on the geology and attendant heterogeneity retained in the fluid flow model. Region-based modeling of the PRB incorporates 28000 wells correlated across a 70,000 Km2 area, 2 km thick on average. Within this basin, five of the most productive RCs were identified from production history and placed in a fourfold stratigraphic framework (second- through fourth-order cycles). Within the small- scale 4th-order sequences (30-150-m thick, 16 total), sedimentation regions, each corresponding to an EOD, are defined by thickness, lithology and core-calibrated well-log patterns. This talk illustrates the workflow by focusing on one of the 16 layers in the basin-scale model. Isopach maps from this sample layer conform to depositional patterns confirmed through definition of five core-calibrated, well-log defined sedimentation regions. Lithology distributions also conform to thickness trends in nearshore deltas, but not in offshore regions, where sand-rich and sheet-like, but thin-bedded sandstones are flanked by mud-rich intervals of equivalent thickness. These maps represent sedimentation patterns confined by basal erosional sequence boundary and basin-wide bentonite, yet containing up to seven high-frequency sequence boundaries. To illustrate over simplification problems in this same layer, a 14000 km2 sample area is 600 km3 and using standard averaging methods, which are considered to be geologic in origin, the CPV is 16 km3. However, averaging increases connectivity with high CPV more uniformly distributed; significantly, the key mud belt region separating nearshore from offshore sandstones is not represented. Region-based modeling of this layer yields 13 km3 (110 Bbl). Furthermore, significant vertical leakage may exist from the 20000 well penetrations and faults and fractures along the western basin margin. This example illustrates the importance of accurately characterizing heterogeneity and distributing CPV using sedimentation regions.

Compilation of a Global Emission Inventory from 1980 to 2000 for Global Model Simulations of the Long-term Trend of Tropospheric Aerosols

NASA Technical Reports Server (NTRS)

Diehl, T. L.; Mian, Chin; Bond, T. C.; Carn, S. A.; Duncan, B. N.; Krotkov, N. A.; Streets, D. G.

2007-01-01

The approach to create a comprehensive emission inventory for the time period 1980 to 2000 is described in this paper. We have recently compiled an emission database, which we will use for a 21 year simulation of tropospheric aerosols with the GOCART model. Particular attention was paid to the time-dependent SO2, black carbon and organic carbon aerosol emissions. For the emission of SO2 from sporadically erupting volcanoes, we assembled emission data from the Global Volcanism Program of the Smithsonian Institution, using the VEI to derive the volcanic cloud height and the SO2 amount, and amended this dataset by the SO2 emission data from the TOMS instrument when available. 3-dimensional aircraft emission data was obtained for a number of years from the AEAP project, converted from burned fuel to SO2 and interpolated to each year, taking the sparsity of the flight patterns into account. Other anthopogenic SO2 emissions are based on gridded emissions from the EDGAR 2000 database (excluding sources from aircraft, biomass burning and international ship traffic), which were scaled to individual years with country/regional based emission inventories. Gridded SO2 emissions from international ship traffic for 2000 and the scaling factors for other years are from [Eyring et al., 2005]. We used gridded anthropogenic black and organic carbon emissions for 1996 [Bond et al., 2005], again excluding aircraft, biomass burning and ship sources. These emissions were scaled with regional based emission inventories from 1980 to 2000 to derive gridded emissions for each year. The biomass burning emissions are based on a climatology, which is scaled with regional scaling factors derived from the TOMS aerosol index and the AVHRR/ATSR fire counts to each year [Duncan et al., 2003]. Details on the integration of the information from the various sources will be provided and the distribution patterns and total emissions in the final product will be discussed.

Compilation of a Global Emission Inventory from 1980 to 2000 for Global Model Simulations of the Long-term Trend of Tropospheric Aerosols

NASA Technical Reports Server (NTRS)

Diehl, Thomas L.; Chin, Mian; Bond, Tami C.; Carn, SImon A.; Duncan, Bryan N.; Krotkov, Nickolay A.; Streets, David G.

2006-01-01

The approach to create a comprehensive emission inventory for the time period 1980 to 2000 is described in this paper. We have recently compiled an emission database, which we will use for a 21 year simulation of tropospheric aerosols with the GOCART model. Particular attention was paid to the time-dependent SO2, black carbon and organic carbon aerosol emissions. For the emission of SO2 from sporadically erupting volcanoes, we assembled emission data from the Global Volcanism Program of the Smithsonian Institution, using the VEI to derive the volcanic cloud height and the SO2 amount, and amended this dataset by the SO2 emission data from the TOMS instrument when available. 3-dimensional aircraft emission data was obtained for a number of years from the AEAP project, converted from burned fuel to SO2 and interpolated to each year, taking the sparsity of the flight patterns into account. Other anthropogenic SO2 emissions are based on gridded emissions from the EDGAR 2000 database (excluding sources from aircraft, biomass burning and international ship traffic), which were scaled to individual years with country/regional based emission inventories. Gridded SO2 emissions from international ship traffic for 2000 and the scaling factors for other years are from [Eyring et al., 2005]. We used gridded anthropogenic black and organic carbon emissions for 1996 [Bond et al., 2005], again excluding aircraft, biomass burning and ship sources. These emissions were scaled with regional based emission inventories from 1980 to 2000 to derive gridded emissions for each year. The biomass burning emissions are based on a climatology, which is scaled with regional scaling factors derived from the TOMS aerosol index and the AVHRR/ASTR fire counts to each year [Duncan et al., 2003]. Details on the integration of the information from the various sources will be provided and the distribution patterns and total emissions in the final product will be discussed.

The role of electron heat flux in guide-field magnetic reconnection

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

Hesse, Michael; Kuznetsova, Masha; Birn, Joachim

2004-12-01

A combination of analytical theory and particle-in-cell simulations are employed in order to investigate the electron dynamics near and at the site of guide field magnetic reconnection. A detailed analysis of the contributions to the reconnection electric field shows that both bulk inertia and pressure-based quasiviscous processes are important for the electrons. Analytic scaling demonstrates that conventional approximations for the electron pressure tensor behavior in the dissipation region fail, and that heat flux contributions need to be accounted for. Based on the evolution equation of the heat flux three tensor, which is derived in this paper, an approximate form ofmore » the relevant heat flux contributions to the pressure tensor is developed, which reproduces the numerical modeling result reasonably well. Based on this approximation, it is possible to develop a scaling of the electron current layer in the central dissipation region. It is shown that the pressure tensor contributions become important at the scale length defined by the electron Larmor radius in the guide magnetic field.« less

Major- and Trace-Element Concentrations in Soils from Northern California: Results from the Geochemical Landscapes Project Pilot Study

USGS Publications Warehouse

Morrison, Jean M.; Goldhaber, Martin B.; Holloway, JoAnn M.; Smith, David B.

2008-01-01

In 2004, the U.S. Geological Survey (USGS), the Geological Survey of Canada (GSC), and the Mexican Geological Survey (Servicio Geologico Mexicano, or SGM) initiated pilot studies in preparation for a soil geochemical survey of North America called the Geochemical Landscapes Project. The purpose of this project is to provide a better understanding of the variability in chemical composition of soils in North America. The data produced by this survey will be used to construct baseline geochemical maps for regions within the continent. Two initial pilot studies were conducted: (1) a continental-scale study involving a north-south and east-west transect across North America and (2) a regional-scale study. The pilot studies were intended to test and refine sample design, sampling protocols, and field logistics for the full continental soils geochemical survey. Smith and others (2005) reported the results from the continental-scale pilot study. The regional-scale California study was designed to represent more detailed, higher resolution geochemical investigations in a region of particular interest that was identified from the low-sample-density continental-scale survey. A 20,000-km2 area of northern California (fig. 1), representing a wide variety of topography, climate, and ecoregions, was chosen for the regional-scale pilot study. This study area also contains diverse geology and soil types and supports a wide range of land uses including agriculture in the Sacramento Valley, forested areas in portions of the Sierra Nevada, and urban/suburban centers such as Sacramento, Davis, and Stockton. Also of interest are potential effects on soil geochemistry from historical hard rock and placer gold mining in the foothills of the Sierra Nevada, historical mercury mining in the Coast Range, and mining of base-metal sulfide deposits in the Klamath Mountains to the north. This report presents the major- and trace-element concentrations from the regional-scale soil geochemical survey in northern California.

Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

NASA Astrophysics Data System (ADS)

Kashid, Satishkumar S.; Maity, Rajib

2012-08-01

SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different 'homogeneous monsoon regions'.

Continental hydrosystem modelling: the concept of nested stream-aquifer interfaces

NASA Astrophysics Data System (ADS)

Flipo, N.; Mouhri, A.; Labarthe, B.; Biancamaria, S.; Rivière, A.; Weill, P.

2014-08-01

Coupled hydrological-hydrogeological models, emphasising the importance of the stream-aquifer interface, are more and more used in hydrological sciences for pluri-disciplinary studies aiming at investigating environmental issues. Based on an extensive literature review, stream-aquifer interfaces are described at five different scales: local [10 cm-~10 m], intermediate [~10 m-~1 km], watershed [10 km2-~1000 km2], regional [10 000 km2-~1 M km2] and continental scales [>10 M km2]. This led us to develop the concept of nested stream-aquifer interfaces, which extends the well-known vision of nested groundwater pathways towards the surface, where the mixing of low frequency processes and high frequency processes coupled with the complexity of geomorphological features and heterogeneities creates hydrological spiralling. This conceptual framework allows the identification of a hierarchical order of the multi-scale control factors of stream-aquifer hydrological exchanges, from the larger scale to the finer scale. The hyporheic corridor, which couples the river to its 3-D hyporheic zone, is then identified as the key component for scaling hydrological processes occurring at the interface. The identification of the hyporheic corridor as the support of the hydrological processes scaling is an important step for the development of regional studies, which is one of the main concerns for water practitioners and resources managers. In a second part, the modelling of the stream-aquifer interface at various scales is investigated with the help of the conductance model. Although the usage of the temperature as a tracer of the flow is a robust method for the assessment of stream-aquifer exchanges at the local scale, there is a crucial need to develop innovative methodologies for assessing stream-aquifer exchanges at the regional scale. After formulating the conductance model at the regional and intermediate scales, we address this challenging issue with the development of an iterative modelling methodology, which ensures the consistency of stream-aquifer exchanges between the intermediate and regional scales. Finally, practical recommendations are provided for the study of the interface using the innovative methodology MIM (Measurements-Interpolation-Modelling), which is graphically developed, scaling in space the three pools of methods needed to fully understand stream-aquifer interfaces at various scales. In the MIM space, stream-aquifer interfaces that can be studied by a given approach are localised. The efficiency of the method is demonstrated with two examples. The first one proposes an upscaling framework, structured around river reaches of ~10-100 m, from the local to the watershed scale. The second example highlights the usefulness of space borne data to improve the assessment of stream-aquifer exchanges at the regional and continental scales. We conclude that further developments in modelling and field measurements have to be undertaken at the regional scale to enable a proper modelling of stream-aquifer exchanges from the local to the continental scale.

Integrated Modeling for Watershed Ecosystem Services Assessment and Forecasting

EPA Science Inventory

Regional scale watershed management decisions must be informed by the science-based relationship between anthropogenic activities on the landscape and the change in ecosystem structure, function, and services that occur as a result. We applied process-based models that represent...

Draft reference grid cells for emergency response reconnaissance developed for use by the US Environmental Protection Agency [ER.QUADS6K_EPA

EPA Pesticide Factsheets

Draft reference grid cells for emergency response reconnaissance developed for use by the US Environmental Protection Agency. Grid cells are based on densification of the USGS Quarterquad (1:12,000 scale or 12K) grids for the continental United States, Alaska, Hawaii and Puerto Rico and are roughly equivalent to 1:6000 scale (6K) quadrangles approximately 2 miles long on each side. Note: This file is >80MB in size. Regional subsets have been created from this national file that include a 20 mile buffer of tiles around each EPA Region. To access the regional subsets, go to http://geodata.epa.gov/OSWER/6kquads_epa.zip and select the name of the file that corresponds to your region of interest (e.g. 6kquadr1.zip is the name of the file created for EPA Region 1).

Extreme Precipitation and High-Impact Landslides

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Huffman, George; Peters-Lidard, Christa

2012-01-01

It is well known that extreme or prolonged rainfall is the dominant trigger of landslides; however, there remain large uncertainties in characterizing the distribution of these hazards and meteorological triggers at the global scale. Researchers have evaluated the spatiotemporal distribution of extreme rainfall and landslides at local and regional scale primarily using in situ data, yet few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This research uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from Tropical Rainfall Measuring Mission (TRMM) data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurence of precipitation and rainfall-triggered landslides globally. The GLC, available from 2007 to the present, contains information on reported rainfall-triggered landslide events around the world using online media reports, disaster databases, etc. When evaluating this database, we observed that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This research also considers the sources for this extreme rainfall, citing teleconnections from ENSO as likely contributors to regional precipitation variability. This work demonstrates the potential for using satellite-based precipitation estimates to identify potentially active landslide areas at the global scale in order to improve landslide cataloging and quantify landslide triggering at daily, monthly and yearly time scales.

Large-scale broadband absorber based on metallic tungsten nanocone structure

NASA Astrophysics Data System (ADS)

Wang, Jiaxing; Liang, Yuzhang; Huo, Pengcheng; Wang, Daopeng; Tan, Jun; Xu, Ting

2017-12-01

We report a broadband tungsten absorber based on a nanocone metallic resonant structure fabricated by self-assembly nanosphere lithography. In experimental demonstration, the fabricated absorber has more than 90% average absorption efficiency and shows superior angular tolerance in the entire visible and near-infrared spectral region. We envision that this large-scale nanostructured broadband optical absorber would find great potential in the applications of high performance optoelectronic platforms and solar-thermal energy harvesting systems.

High-Resolution Climate Data Visualization through GIS- and Web-based Data Portals

NASA Astrophysics Data System (ADS)

WANG, X.; Huang, G.

2017-12-01

Sound decisions on climate change adaptation rely on an in-depth assessment of potential climate change impacts at regional and local scales, which usually requires finer resolution climate projections at both spatial and temporal scales. However, effective downscaling of global climate projections is practically difficult due to the lack of computational resources and/or long-term reference data. Although a large volume of downscaled climate data has been make available to the public, how to understand and interpret the large-volume climate data and how to make use of the data to drive impact assessment and adaptation studies are still challenging for both impact researchers and decision makers. Such difficulties have become major barriers preventing informed climate change adaptation planning at regional scales. Therefore, this research will explore new GIS- and web-based technologies to help visualize the large-volume regional climate data with high spatiotemporal resolutions. A user-friendly public data portal, named Climate Change Data Portal (CCDP, http://ccdp.network), will be established to allow intuitive and open access to high-resolution regional climate projections at local scales. The CCDP offers functions of visual representation through geospatial maps and data downloading for a variety of climate variables (e.g., temperature, precipitation, relative humidity, solar radiation, and wind) at multiple spatial resolutions (i.e., 25 - 50 km) and temporal resolutions (i.e., annual, seasonal, monthly, daily, and hourly). The vast amount of information the CCDP encompasses can provide a crucial basis for assessing impacts of climate change on local communities and ecosystems and for supporting better decision making under a changing climate.

A refined regional modeling approach for the Corn Belt - Experiences and recommendations for large-scale integrated modeling

NASA Astrophysics Data System (ADS)

Panagopoulos, Yiannis; Gassman, Philip W.; Jha, Manoj K.; Kling, Catherine L.; Campbell, Todd; Srinivasan, Raghavan; White, Michael; Arnold, Jeffrey G.

2015-05-01

Nonpoint source pollution from agriculture is the main source of nitrogen and phosphorus in the stream systems of the Corn Belt region in the Midwestern US. This region is comprised of two large river basins, the intensely row-cropped Upper Mississippi River Basin (UMRB) and Ohio-Tennessee River Basin (OTRB), which are considered the key contributing areas for the Northern Gulf of Mexico hypoxic zone according to the US Environmental Protection Agency. Thus, in this area it is of utmost importance to ensure that intensive agriculture for food, feed and biofuel production can coexist with a healthy water environment. To address these objectives within a river basin management context, an integrated modeling system has been constructed with the hydrologic Soil and Water Assessment Tool (SWAT) model, capable of estimating river basin responses to alternative cropping and/or management strategies. To improve modeling performance compared to previous studies and provide a spatially detailed basis for scenario development, this SWAT Corn Belt application incorporates a greatly refined subwatershed structure based on 12-digit hydrologic units or 'subwatersheds' as defined by the US Geological Service. The model setup, calibration and validation are time-demanding and challenging tasks for these large systems, given the scale intensive data requirements, and the need to ensure the reliability of flow and pollutant load predictions at multiple locations. Thus, the objectives of this study are both to comprehensively describe this large-scale modeling approach, providing estimates of pollution and crop production in the region as well as to present strengths and weaknesses of integrated modeling at such a large scale along with how it can be improved on the basis of the current modeling structure and results. The predictions were based on a semi-automatic hydrologic calibration approach for large-scale and spatially detailed modeling studies, with the use of the Sequential Uncertainty Fitting algorithm (SUFI-2) and the SWAT-CUP interface, followed by a manual water quality calibration on a monthly basis. The refined modeling approach developed in this study led to successful predictions across most parts of the Corn Belt region and can be used for testing pollution mitigation measures and agricultural economic scenarios, providing useful information to policy makers and recommendations on similar efforts at the regional scale.

REGIONAL OXIDANT MODEL (ROM) USER'S GUIDE, PART 2: THE ROM PREPROCESSOR NETWORK

EPA Science Inventory

The Regional Oxidant Model (ROM) determines hourly concentrations and fates of zone and 34 other chemical species over a scale of 1000 km x 1000 km for ozone "episodes" of up to one month's duration. he model structure, based on phenomenological concepts, consists of 3 1/2 layers...

DYNAMIC EVALUATION OF REGIONAL AIR QUALITY MODELS: ASSESSING CHANGES TO O 3 STEMMING FROM CHANGES IN EMISSIONS AND METEOROLOGY

EPA Science Inventory

Regional-scale air quality models are used to estimate the response of air pollutants to potential emission control strategies as part of the decision-making process. Traditionally, the model predicted pollutant concentrations are evaluated for the “base case” to assess a model’s...

Utility of thermal-based two-source energy balance model for estimating vineyard evapotranspiration at field and regional scales

USDA-ARS?s Scientific Manuscript database

The prolonged drought in much of California over the last few years, particularly in the Central Valley region, has caused severe reduction in water reservoir levels and a major depletion of ground water by agriculture. Dramatic improvements in water and irrigation management practices are critical ...

Meta-modeling soil organic carbon sequestration potential and its application at regional scale.

PubMed

Luo, Zhongkui; Wang, Enli; Bryan, Brett A; King, Darran; Zhao, Gang; Pan, Xubin; Bende-Michl, Ulrike

2013-03-01

Upscaling the results from process-based soil-plant models to assess regional soil organic carbon (SOC) change and sequestration potential is a great challenge due to the lack of detailed spatial information, particularly soil properties. Meta-modeling can be used to simplify and summarize process-based models and significantly reduce the demand for input data and thus could be easily applied on regional scales. We used the pre-validated Agricultural Production Systems sIMulator (APSIM) to simulate the impact of climate, soil, and management on SOC at 613 reference sites across Australia's cereal-growing regions under a continuous wheat system. We then developed a simple meta-model to link the APSIM-modeled SOC change to primary drivers, i.e., the amount of recalcitrant SOC, plant available water capacity of soil, soil pH, and solar radiation, temperature, and rainfall in the growing season. Based on high-resolution soil texture data and 8165 climate data points across the study area, we used the meta-model to assess SOC sequestration potential and the uncertainty associated with the variability of soil characteristics. The meta-model explained 74% of the variation of final SOC content as simulated by APSIM. Applying the meta-model to Australia's cereal-growing regions reveals regional patterns in SOC, with higher SOC stock in cool, wet regions. Overall, the potential SOC stock ranged from 21.14 to 152.71 Mg/ha with a mean of 52.18 Mg/ha. Variation of soil properties induced uncertainty ranging from 12% to 117% with higher uncertainty in warm, wet regions. In general, soils in Australia's cereal-growing regions under continuous wheat production were simulated as a sink of atmospheric carbon dioxide with a mean sequestration potential of 8.17 Mg/ha.

An upscaled two-equation model of transport in porous media through unsteady-state closure of volume averaged formulations

NASA Astrophysics Data System (ADS)

Chaynikov, S.; Porta, G.; Riva, M.; Guadagnini, A.

2012-04-01

We focus on a theoretical analysis of nonreactive solute transport in porous media through the volume averaging technique. Darcy-scale transport models based on continuum formulations typically include large scale dispersive processes which are embedded in a pore-scale advection diffusion equation through a Fickian analogy. This formulation has been extensively questioned in the literature due to its inability to depict observed solute breakthrough curves in diverse settings, ranging from the laboratory to the field scales. The heterogeneity of the pore-scale velocity field is one of the key sources of uncertainties giving rise to anomalous (non-Fickian) dispersion in macro-scale porous systems. Some of the models which are employed to interpret observed non-Fickian solute behavior make use of a continuum formulation of the porous system which assumes a two-region description and includes a bimodal velocity distribution. A first class of these models comprises the so-called ''mobile-immobile'' conceptualization, where convective and dispersive transport mechanisms are considered to dominate within a high velocity region (mobile zone), while convective effects are neglected in a low velocity region (immobile zone). The mass exchange between these two regions is assumed to be controlled by a diffusive process and is macroscopically described by a first-order kinetic. An extension of these ideas is the two equation ''mobile-mobile'' model, where both transport mechanisms are taken into account in each region and a first-order mass exchange between regions is employed. Here, we provide an analytical derivation of two region "mobile-mobile" meso-scale models through a rigorous upscaling of the pore-scale advection diffusion equation. Among the available upscaling methodologies, we employ the Volume Averaging technique. In this approach, the heterogeneous porous medium is supposed to be pseudo-periodic, and can be represented through a (spatially) periodic unit cell. Consistently with the two-region model working hypotheses, we subdivide the pore space into two volumes, which we select according to the features of the local micro-scale velocity field. Assuming separation of the scales, the mathematical development associated with the averaging method in the two volumes leads to a generalized two-equation model. The final (upscaled) formulation includes the standard first order mass exchange term together with additional terms, which we discuss. Our developments allow to identify the assumptions which are usually implicitly embedded in the usual adoption of a two region mobile-mobile model. All macro-scale properties introduced in this model can be determined explicitly from the pore-scale geometry and hydrodynamics through the solution of a set of closure equations. We pursue here an unsteady closure of the problem, leading to the occurrence of nonlocal (in time) terms in the upscaled system of equations. We provide the solution of the closure problems for a simple application documenting the time dependent and the asymptotic behavior of the system.

Salient object detection based on multi-scale contrast.

PubMed

Wang, Hai; Dai, Lei; Cai, Yingfeng; Sun, Xiaoqiang; Chen, Long

2018-05-01

Due to the development of deep learning networks, a salient object detection based on deep learning networks, which are used to extract the features, has made a great breakthrough compared to the traditional methods. At present, the salient object detection mainly relies on very deep convolutional network, which is used to extract the features. In deep learning networks, an dramatic increase of network depth may cause more training errors instead. In this paper, we use the residual network to increase network depth and to mitigate the errors caused by depth increase simultaneously. Inspired by image simplification, we use color and texture features to obtain simplified image with multiple scales by means of region assimilation on the basis of super-pixels in order to reduce the complexity of images and to improve the accuracy of salient target detection. We refine the feature on pixel level by the multi-scale feature correction method to avoid the feature error when the image is simplified at the above-mentioned region level. The final full connection layer not only integrates features of multi-scale and multi-level but also works as classifier of salient targets. The experimental results show that proposed model achieves better results than other salient object detection models based on original deep learning networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

The length of the glaciers in the world - a straightforward method for the automated calculation of glacier center lines

NASA Astrophysics Data System (ADS)

Machguth, H.; Huss, M.

2014-05-01

Glacier length is an important measure of glacier geometry but global glacier inventories are mostly lacking length data. Only recently semi-automated approaches to measure glacier length have been developed and applied regionally. Here we present a first global assessment of glacier length using a fully automated method based on glacier surface slope, distance to the glacier margins and a set of trade-off functions. The method is developed for East Greenland, evaluated for the same area as well as for Alaska, and eventually applied to all ∼200 000 glaciers around the globe. The evaluation highlights accurately calculated glacier length where DEM quality is good (East Greenland) and limited precision on low quality DEMs (parts of Alaska). Measured length of very small glaciers is subject to a certain level of ambiguity. The global calculation shows that only about 1.5% of all glaciers are longer than 10 km with Bering Glacier (Alaska/Canada) being the longest glacier in the world at a length of 196 km. Based on model output we derive global and regional area-length scaling laws. Differences among regional scaling parameters appear to be related to characteristics of topography and glacier mass balance. The present study adds glacier length as a central parameter to global glacier inventories. Global and regional scaling laws might proof beneficial in conceptual glacier models.

Leaching of biocides from building facades: Upscaling of a local two-region leaching model to the city scale

NASA Astrophysics Data System (ADS)

Coutu, S.; Rota, C.; Rossi, L.; Barry, D. A.

2011-12-01

Facades are protected by paints that contain biocides as protection against degradation. These biocides are leached by rainfall (albeit at low concentrations). At the city scale, however, the surface area of building facades is significant, and leached biocides are a potential environmental risk to receiving waters. A city-scale biocide-leaching model was developed based on two main steps. In the first step, laboratory experiments on a single facade were used to calibrate and validate a 1D, two-region phenomenological model of biocide leaching. The same data set was analyzed independently by another research group who found empirically that biocide leachate breakthrough curves were well represented by a sum of two exponentials. Interestingly, the two-region model was found analytically to reproduce this functional form as a special case. The second step in the method is site-specific, and involves upscaling the validated single facade model to a particular city. In this step, (i) GIS-based estimates of facade heights and areas are deduced using the city's cadastral data, (ii) facade flow is estimated using local meteorological data (rainfall, wind direction) and (iii) paint application rates are modeled as a stochastic process based on manufacturers' recommendations. The methodology was applied to Lausanne, Switzerland, a city of about 200,000 inhabitants. Approximately 30% of the annually applied mass of biocides was estimated to be released to the environment.

Multi-scale landslide hazard assessment: Advances in global and regional methodologies

NASA Astrophysics Data System (ADS)

Kirschbaum, Dalia; Peters-Lidard, Christa; Adler, Robert; Hong, Yang

2010-05-01

The increasing availability of remotely sensed surface data and precipitation provides a unique opportunity to explore how smaller-scale landslide susceptibility and hazard assessment methodologies may be applicable at larger spatial scales. This research first considers an emerging satellite-based global algorithm framework, which evaluates how the landslide susceptibility and satellite derived rainfall estimates can forecast potential landslide conditions. An analysis of this algorithm using a newly developed global landslide inventory catalog suggests that forecasting errors are geographically variable due to improper weighting of surface observables, resolution of the current susceptibility map, and limitations in the availability of landslide inventory data. These methodological and data limitation issues can be more thoroughly assessed at the regional level, where available higher resolution landslide inventories can be applied to empirically derive relationships between surface variables and landslide occurrence. The regional empirical model shows improvement over the global framework in advancing near real-time landslide forecasting efforts; however, there are many uncertainties and assumptions surrounding such a methodology that decreases the functionality and utility of this system. This research seeks to improve upon this initial concept by exploring the potential opportunities and methodological structure needed to advance larger-scale landslide hazard forecasting and make it more of an operational reality. Sensitivity analysis of the surface and rainfall parameters in the preliminary algorithm indicates that surface data resolution and the interdependency of variables must be more appropriately quantified at local and regional scales. Additionally, integrating available surface parameters must be approached in a more theoretical, physically-based manner to better represent the physical processes underlying slope instability and landslide initiation. Several rainfall infiltration and hydrological flow models have been developed to model slope instability at small spatial scales. This research investigates the potential of applying a more quantitative hydrological model to larger spatial scales, utilizing satellite and surface data inputs that are obtainable over different geographic regions. Due to the significant role that data and methodological uncertainties play in the effectiveness of landslide hazard assessment outputs, the methodology and data inputs are considered within an ensemble uncertainty framework in order to better resolve the contribution and limitations of model inputs and to more effectively communicate the model skill for improved landslide hazard assessment.

Multiscale Bayesian neural networks for soil water content estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.; Springer, Everett P.

2008-08-01

Artificial neural networks (ANN) have been used for some time now to estimate soil hydraulic parameters from other available or more easily measurable soil properties. However, most such uses of ANNs as pedotransfer functions (PTFs) have been at matching spatial scales (1:1) of inputs and outputs. This approach assumes that the outputs are only required at the same scale as the input data. Unfortunately, this is rarely true. Different hydrologic, hydroclimatic, and contaminant transport models require soil hydraulic parameter data at different spatial scales, depending upon their grid sizes. While conventional (deterministic) ANNs have been traditionally used in these studies, the use of Bayesian training of ANNs is a more recent development. In this paper, we develop a Bayesian framework to derive soil water retention function including its uncertainty at the point or local scale using PTFs trained with coarser-scale Soil Survey Geographic (SSURGO)-based soil data. The approach includes an ANN trained with Bayesian techniques as a PTF tool with training and validation data collected across spatial extents (scales) in two different regions in the United States. The two study areas include the Las Cruces Trench site in the Rio Grande basin of New Mexico, and the Southern Great Plains 1997 (SGP97) hydrology experimental region in Oklahoma. Each region-specific Bayesian ANN is trained using soil texture and bulk density data from the SSURGO database (scale 1:24,000), and predictions of the soil water contents at different pressure heads with point scale data (1:1) inputs are made. The resulting outputs are corrected for bias using both linear and nonlinear correction techniques. The results show good agreement between the soil water content values measured at the point scale and those predicted by the Bayesian ANN-based PTFs for both the study sites. Overall, Bayesian ANNs coupled with nonlinear bias correction are found to be very suitable tools for deriving soil hydraulic parameters at the local/fine scale from soil physical properties at coarser-scale and across different spatial extents. This approach could potentially be used for soil hydraulic properties estimation and downscaling.

The SERGISAI procedure for seismic risk assessment

NASA Astrophysics Data System (ADS)

Zonno, G.; Garcia-Fernandez, M.; Jimenez, M.J.; Menoni, S.; Meroni, F.; Petrini, V.

The European project SERGISAI developed a computational tool where amethodology for seismic risk assessment at different geographical scales hasbeen implemented. Experts of various disciplines, including seismologists,engineers, planners, geologists, and computer scientists, co-operated in anactual multidisciplinary process to develop this tool. Standard proceduralcodes, Geographical Information Systems (GIS), and Artificial Intelligence(AI) techniques compose the whole system, that will enable the end userto carry out a complete seismic risk assessment at three geographical scales:regional, sub-regional and local. At present, single codes or models thathave been incorporated are not new in general, but the modularity of theprototype, based on a user-friendly front-end, offers potential users thepossibility of updating or replacing any code or model if desired. Theproposed procedure is a first attempt to integrate tools, codes and methodsfor assessing expected earthquake damage, and it was mainly designedto become a useful support for civil defence and land use planning agencies.Risk factors have been treated in the most suitable way for each one, interms of level of detail, kind of parameters and units of measure.Identifying various geographical scales is not a mere question of dimension;since entities to be studied correspond to areas defined by administrativeand geographical borders. The procedure was applied in the following areas:Toscana in Italy, for the regional scale, the Garfagnana area in Toscana, forthe sub-regional scale, and a part of Barcelona city, Spain, for the localscale.

Utility of a Two-source Energy Balance Approach for Daily Mapping of Landsat-scale Fluxes Over Irrigated Agriculture in a Desert Environment

NASA Astrophysics Data System (ADS)

Houborg, R.; McCabe, M. F.; Rosas Aguilar, J.; Anderson, M. C.; Hain, C.

2014-12-01

The Middle East and North Africa (MENA) region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. Enhanced satellite-based monitoring systems are needed for aiding local water resource and agricultural management activities in these data poor arid environments. A multi-sensor and multi-scale land-surface flux monitoring capacity is being implemented over parts of MENA in order to provide meaningful decision support at relevant spatiotemporal scales. The integrated modeling system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (Landsat and MODIS; MODerate resolution Imaging Spectroradiometer) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of land surface fluxes down to sub-field scale (i.e. 30 m). Within this modeling system, thermal infrared satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and error-prone soil surface characterizations. In this study, the integrated ALEXI-DisALEXI-STARFM framework is applied over an irrigated agricultural region in Saudi Arabia, and the daily estimates of Landsat scale water, energy and carbon fluxes are evaluated against available flux tower observations and other independent in-situ and satellite-based records. The study addresses the challenges associated with time-continuous sub-field scale mapping of land-surface fluxes in a harsh desert environment, and looks into the optimization of model descriptions and parameterizations and meteorological forcing and vegetation inputs for application over these regions.

Cost-effective sampling of ¹³⁷Cs-derived net soil redistribution: part 1--estimating the spatial mean across scales of variation.

PubMed

Li, Y; Chappell, A; Nyamdavaa, B; Yu, H; Davaasuren, D; Zoljargal, K

2015-03-01

The (137)Cs technique for estimating net time-integrated soil redistribution is valuable for understanding the factors controlling soil redistribution by all processes. The literature on this technique is dominated by studies of individual fields and describes its typically time-consuming nature. We contend that the community making these studies has inappropriately assumed that many (137)Cs measurements are required and hence estimates of net soil redistribution can only be made at the field scale. Here, we support future studies of (137)Cs-derived net soil redistribution to apply their often limited resources across scales of variation (field, catchment, region etc.) without compromising the quality of the estimates at any scale. We describe a hybrid, design-based and model-based, stratified random sampling design with composites to estimate the sampling variance and a cost model for fieldwork and laboratory measurements. Geostatistical mapping of net (1954-2012) soil redistribution as a case study on the Chinese Loess Plateau is compared with estimates for several other sampling designs popular in the literature. We demonstrate the cost-effectiveness of the hybrid design for spatial estimation of net soil redistribution. To demonstrate the limitations of current sampling approaches to cut across scales of variation, we extrapolate our estimate of net soil redistribution across the region, show that for the same resources, estimates from many fields could have been provided and would elucidate the cause of differences within and between regional estimates. We recommend that future studies evaluate carefully the sampling design to consider the opportunity to investigate (137)Cs-derived net soil redistribution across scales of variation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Utility of an image-based canopy reflectance modeling tool for remote estimation and LAI and leaf chlorophyll content at regional scales

USDA-ARS?s Scientific Manuscript database

Radiance data recorded by remote sensors function as a unique source for monitoring the terrestrial biosphere and vegetation dynamics at a range of spatial and temporal scales. A key challenge is to relate the remote sensing signal to critical variables describing land surface vegetation canopies su...

Fine flow structures in the transition region small-scale loops

NASA Astrophysics Data System (ADS)

Yan, L.; Peter, H.; He, J.; Wei, Y.

2016-12-01

The observation and model have suggested that the transition region EUV emission from the quiet sun region is contributed by very small scale loops which have not been resolved. Recently, the observation from IRIS has revealed that this kind of small scale loops. Based on the high resolution spectral and imaging observation from IRIS, much more detail work needs to be done to reveal the fine flow features in this kind of loop to help us understand the loop heating. Here, we present a detail statistical study of the spatial and temporal evolution of Si IV line profiles of small scale loops and report the spectral features: there is a transition from blue (red) wing enhancement dominant to red (blue) wing enhancement dominant along the cross-section of the loop, which is independent of time. This feature appears as the loop appear and disappear as the loop un-visible. This is probably the signature of helical flow along the loop. The result suggests that the brightening of this kind of loop is probably due to the current dissipation heating in the twisted magnetic field flux tube.

[Characteristics of water and heat fluxes and its footprint climatology on farmland in low hilly region of red soil].

PubMed

Li, Yang; Jing, Yuan Shu; Qin, Ben Ben

2017-01-01

The analysis of the characteristics and footprint climatology of farmland water and heat fluxes has great significance to strengthen regional climate resource management and improve the hydrothermal resource utilization in the region of red soil. Based on quality controlled data from large aperture scintillometer and automatic meteorological station in hilly region of red soil, this paper analyzed in detail the characteristics of farmland water and heat fluxes at different temporal scales and the corresponding source area distribution of flux measurement in the non-rainy season and crop growth period in hilly region of red soil. The results showed that the diurnal variation of water and heat fluxes showed a unimodal trend, but compared with the sunny day, the diurnal variation curves fluctuated more complicatedly on cloudy day. In the whole, either ten-day periods or month scale, the water and heat fluxes were greater in August than in September, while the net radiation flux was more distributed to latent heat exchange. The proportion of net radiation to latent heat flux decreased in September compared to August, but the sensible heat flux was vice versa. With combined effects of weather conditions (particularly wind), stability, and surface condition, the source areas of flux measurement at different temporal scales showed different distribution characteristics. Combined with the underlying surface crops, the source areas at different temporal scales also had different contribution sources.

Magnitude of anthropogenic phosphorus storage in the agricultural production and the waste management systems at the regional and country scales.

PubMed

Chowdhury, Rubel Biswas; Chakraborty, Priyanka

2016-08-01

Based on a systematic review of 17 recent substance flow analyses of phosphorus (P) at the regional and country scales, this study presents an assessment of the magnitude of anthropogenic P storage in the agricultural production and the waste management systems to identify the potential for minimizing unnecessary P storage to reduce the input of P as mineral fertilizer and the loss of P. The assessment indicates that in case of all (6) P flow analyses at the regional scale, the combined mass of annual P storage in the agricultural production and the waste management systems is greater than 50 % of the mass of annual P inflow as mineral fertilizer in the agricultural production system, while this is close to or more than 100 % in case of half of these analyses. At the country scale, in case of the majority (7 out of 11) of analyses, the combined mass of annual P storage in the agricultural production and the waste management systems has been found to be roughly equivalent or greater than 100 % of the mass of annual P inflow as mineral fertilizer in the agricultural production system, while it ranged from 30 to 60 % in the remaining analyses. A simple scenario analysis has revealed that the annual storage of P in this manner over 100 years could result in the accumulation of a massive amount of P in the agricultural production and the waste management systems at both the regional and country scales. This study suggests that sustainable P management initiatives at the regional and country scales should put more emphasis on minimizing unwanted P storage in the agricultural production and the waste management systems.

Multi-platform operational validation of the Western Mediterranean SOCIB forecasting system

NASA Astrophysics Data System (ADS)

Juza, Mélanie; Mourre, Baptiste; Renault, Lionel; Tintoré, Joaquin

2014-05-01

The development of science-based ocean forecasting systems at global, regional, and local scales can support a better management of the marine environment (maritime security, environmental and resources protection, maritime and commercial operations, tourism, ...). In this context, SOCIB (the Balearic Islands Coastal Observing and Forecasting System, www.socib.es) has developed an operational ocean forecasting system in the Western Mediterranean Sea (WMOP). WMOP uses a regional configuration of the Regional Ocean Modelling System (ROMS, Shchepetkin and McWilliams, 2005) nested in the larger scale Mediterranean Forecasting System (MFS) with a spatial resolution of 1.5-2km. WMOP aims at reproducing both the basin-scale ocean circulation and the mesoscale variability which is known to play a crucial role due to its strong interaction with the large scale circulation in this region. An operational validation system has been developed to systematically assess the model outputs at daily, monthly and seasonal time scales. Multi-platform observations are used for this validation, including satellite products (Sea Surface Temperature, Sea Level Anomaly), in situ measurements (from gliders, Argo floats, drifters and fixed moorings) and High-Frequency radar data. The validation procedures allow to monitor and certify the general realism of the daily production of the ocean forecasting system before its distribution to users. Additionally, different indicators (Sea Surface Temperature and Salinity, Eddy Kinetic Energy, Mixed Layer Depth, Heat Content, transports in key sections) are computed every day both at the basin-scale and in several sub-regions (Alboran Sea, Balearic Sea, Gulf of Lion). The daily forecasts, validation diagnostics and indicators from the operational model over the last months are available at www.socib.es.

Guide for Regional Integrated Assessments: Handbook of Methods and Procedures, Version 5.1. Appendix 1

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia E.; Jones, James W.; Hatfield, Jerry; Antle, John; Ruane, Alex; Boote, Ken; Thorburn, Peter; Valdivia, Roberto; Porter, Cheryl; Janssen, Sander;

The consequences of landscape change on ecological resources: An assessment of the United States mid-Atlantic region, 1973-1993

USGS Publications Warehouse

Jones, K.B.; Neale, A.C.; Wade, T.G.; Wickham, J.D.; Cross, C.L.; Edmonds, C.M.; Loveland, Thomas R.; Nash, M.S.; Riitters, K.H.; Smith, E.R.

2001-01-01

Spatially explicit identification of changes in ecological conditions over large areas is key to targeting and prioritizing areas for environmental protection and restoration by managers at watershed, basin, and regional scales. A critical limitation to this point has been the development of methods to conduct such broad-scale assessments. Field-based methods have proven to be too costly and too inconsistent in their application to make estimates of ecological conditions over large areas. New spatial data derived from satellite imagery and other sources, the development of statistical models relating landscape composition and pattern to ecological endpoints, and geographic information systems (GIS) make it possible to evaluate ecological conditions at multiple scales over broad geographic regions. In this study, we demonstrate the application of spatially distributed models for bird habitat quality and nitrogen yield to streams to assess the consequences of landcover change across the mid-Atlantic region between the 1970s and 1990s. Moreover, we present a way to evaluate spatial concordance between models related to different environmental endpoints. Results of this study should help environmental managers in the mid-Atlantic region target those areas in need of conservation and protection.

Constructing an everywhere and locally relevant predictive model of the West-African critical zone

NASA Astrophysics Data System (ADS)

Hector, B.; Cohard, J. M.; Pellarin, T.; Maxwell, R. M.; Cappelaere, B.; Demarty, J.; Grippa, M.; Kergoat, L.; Lebel, T.; Mamadou, O.; Mougin, E.; Panthou, G.; Peugeot, C.; Vandervaere, J. P.; Vischel, T.; Vouillamoz, J. M.

2017-12-01

Considering water resources and hydrologic hazards, West Africa is among the most vulnerable regions to face both climatic (e.g. with the observed intensification of precipitation) and anthropogenic changes. With +3% of demographic rate, the region experiences rapid land use changes and increased pressure on surface and groundwater resources with observed consequences on the hydrological cycle (water table rise result of the sahelian paradox, increase in flood occurrence, etc.) Managing large hydrosystems (such as transboundary aquifers or rivers basins as the Niger river) requires anticipation of such changes. However, the region significantly lacks observations, for constructing and validating critical zone (CZ) models able to predict future hydrologic regime, but also comprises hydrosystems which encompass strong environmental gradients (e.g. geological, climatic, ecological) with highly different dominating hydrological processes. We address these issues by constructing a high resolution (1 km²) regional scale physically-based model using ParFlow-CLM which allows modeling a wide range of processes without prior knowledge on their relative dominance. Our approach combines multiple scale modeling from local to meso and regional scales within the same theoretical framework. Local and meso-scale models are evaluated thanks to the rich AMMA-CATCH CZ observation database which covers 3 supersites with contrasted environments in Benin (Lat.: 9.8°N), Niger (Lat.: 13.3°N) and Mali (Lat.: 15.3°N). At the regional scale the lack of relevant map of soil hydrodynamic parameters is addressed using remote sensing data assimilation. Our first results show the model's ability to reproduce the known dominant hydrological processes (runoff generation, ET, groundwater recharge…) across the major West-African regions and allow us to conduct virtual experiments to explore the impact of global changes on the hydrosystems. This approach is a first step toward the construction of a reference model to study regional CZ sensitivity to global changes and will help to identify prior parameters required and to construct meta-models for deeper investigations of interactions within the CZ.

Multi-Scale Mapping of Vegetation Biomass

NASA Astrophysics Data System (ADS)

Hudak, A. T.; Fekety, P.; Falkowski, M. J.; Kennedy, R. E.; Crookston, N.; Smith, A. M.; Mahoney, P.; Glenn, N. F.; Dong, J.; Kane, V. R.; Woodall, C. W.

2016-12-01

Vegetation biomass mapping at multiple scales is important for carbon inventory and monitoring, reporting, and verification (MRV). Project-level lidar collections allow biomass estimation with high confidence where associated with field plot measurements. Predictive models developed from such datasets are customarily used to generate landscape-scale biomass maps. We tested the feasibility of predicting biomass in landscapes surveyed with lidar but without field plots, by withholding plot datasets from a reduced model applied to the landscapes, and found support for a generalized model in the northern Idaho ecoregion. We are also upscaling a generalized model to all forested lands in Idaho. Our regional modeling approach is to sample the 30-m biomass predictions from the landscape-scale maps and use them to train a regional biomass model, using Landsat time series, topographic derivatives, and climate variables as predictors. Our regional map validation approach is to aggregate the regional, annual biomass predictions to the county level and compare them to annual county-level biomass summarized independently from systematic, field-based, annual inventories conducted by the US Forest Inventory and Analysis (FIA) Program nationally. A national-scale forest cover map generated independently from 2010 PALSAR data at 25-m resolution is being used to mask non-forest pixels from the aggregations. Effects of climate change on future regional biomass stores are also being explored, using biomass estimates projected from stand-level inventory data collected in the National Forests and comparing them to FIA plot data collected independently on public and private lands, projected under the same climate change scenarios, with disturbance trends extracted from the Landsat time series. Our ultimate goal is to demonstrate, focusing on the ecologically diverse Northwest region of the USA, a carbon monitoring system (CMS) that is accurate, objective, repeatable, and transparent.

The added value of dynamical downscaling in a climate change scenario simulation:A case study for European Alps and East Asia

NASA Astrophysics Data System (ADS)

Im, Eun-Soon; Coppola, Erika; Giorgi, Filippo

2010-05-01

Since anthropogenic climate change is a rather important factor for the future human life all over the planet and its effects are not globally uniform, climate information at regional or local scales become more and more important for an accurate assessment of the potential impact of climate change on societies and ecosystems. High resolution information with suitably fine-scale for resolving complex geographical features could be a critical factor for successful linkage between climate models and impact assessment studies. However, scale mismatch between them still remains major problem. One method for overcoming the resolution limitations of global climate models and for adding regional details to coarse-grid global projections is to use dynamical downscaling by means of a regional climate model. In this study, the ECHAM5/MPI-OM (1.875 degree) A1B scenario simulation has been dynamically downscaled by using two different approaches within the framework of RegCM3 modeling system. First, a mosaic-type parameterization of subgrid-scale topography and land use (Sub-BATS) is applied over the European Alpine region. The Sub-BATS system is composed of 15 km coarse-grid cell and 3 km sub-grid cell. Second, we developed the RegCM3 one-way double-nested system, with the mother domain encompassing the eastern regions of Asia at 60 km grid spacing and the nested domain covering the Korean Peninsula at 20 km grid spacing. By comparing the regional climate model output and the driving global model ECHAM5/MPI-OM output, it is possible to estimate the added value of physically-based dynamical downscaling when for example impact studies at hydrological scale are performed.

Two-stage Keypoint Detection Scheme for Region Duplication Forgery Detection in Digital Images.

PubMed

Emam, Mahmoud; Han, Qi; Zhang, Hongli

2018-01-01

In digital image forensics, copy-move or region duplication forgery detection became a vital research topic recently. Most of the existing keypoint-based forgery detection methods fail to detect the forgery in the smooth regions, rather than its sensitivity to geometric changes. To solve these problems and detect points which cover all the regions, we proposed two steps for keypoint detection. First, we employed the scale-invariant feature operator to detect the spatially distributed keypoints from the textured regions. Second, the keypoints from the missing regions are detected using Harris corner detector with nonmaximal suppression to evenly distribute the detected keypoints. To improve the matching performance, local feature points are described using Multi-support Region Order-based Gradient Histogram descriptor. Based on precision-recall rates and commonly tested dataset, comprehensive performance evaluation is performed. The results demonstrated that the proposed scheme has better detection and robustness against some geometric transformation attacks compared with state-of-the-art methods. © 2017 American Academy of Forensic Sciences.

A method for mapping topsoil field-saturated hydraulic conductivity in the Cévennes-Vivarais region using infiltration tests conducted with different techniques

NASA Astrophysics Data System (ADS)

Braud, Isabelle; Desprats, Jean-François; Ayral, Pierre-Alain; Bouvier, Christophe; Vandervaere, Jean-Pierre

2017-04-01

Topsoil field-saturated hydraulic conductivity, Kfs, is a parameter that controls the partition of rainfall between infiltration and runoff. It is a key parameter in most distributed hydrological models. However, there is a mismatch between the scale of local in situ measurements and the scale at which the parameter is required in models. Therefore it is necessary to design methods to regionally map this parameter at the model scale. The paper propose a method for mapping Kfs in the Cévennes-Vivarais region, south-east France, using more easily available GIS data: geology and land cover. The mapping is based on a data set gathering infiltration tests performed in the area or close to it for more than ten years. The data set is composed of infiltration tests performed using various techniques: Guelph permeameter, double ring and single ring infiltration tests, infiltrometers with multiple suctions. The different methods lead to different orders of magnitude for Kfs rendering the pooling of all the data challenging. Therefore, a method is first proposed to pool the data from the different infiltration methods, leading to a homogenized set of Kfs, based on an equivalent double ring/tension disk infiltration value. Statistical tests showed significant differences in distributions among different geologies and land covers. Thus those variables were retained as proxy for mapping Kfs at the regional scale. This map was compared to a map based on the Rawls and Brakensiek (RB) pedo-transfer function (Manus et al., 2009, Vannier et al., 2016), showing very different patterns between both maps. In addition, RB values did not fit observed values at the plot scale, highlighting that soil texture only is not a good predictor of Kfs. References Manus, C., Anquetin, S., Braud, I., Vandervaere, J.P., Viallet, P., Creutin, J.D., Gaume, E., 2009. A modelling approach to assess the hydrological response of small Mediterranean catchments to the variability of soil characteristics in a context of extreme events. Hydrology and Earth System Sciences, 13: 79-87. Vannier, O., Anquetin, S., Braud, I., 2016. Investigating the role of geology in the hydrological response of Mediterranean catchments prone to flash-floods: regional modelling study and process understanding. Journal of Hydrology, 541 Part A, 158-172.

Comparison Of Landscape-level Carbon Flux Estimates from Budgeting The Planetary Boundary Layer And Footprinting On Remote Sensing Images

NASA Astrophysics Data System (ADS)

Chen, B.; Chen, J. M.; Mo, G.

2006-12-01

Carbon balance estimation at the landscape/regional scale is a challenge because of the heterogeneity of the land surface and the nonlinearity inherent in ecophysiological processes. Two methodologies, a simple atmospheric boundary-layer budgeting method and an integrated modeling method, were explored and compared in this study. Studies of the atmospheric boundary-layer (ABL) budget of CO2 have the potential to provide information on carbon balance of the land surface on a regional scale. Indeed, the surface area of integration by the ABL moving through a tower in one day was estimated to be ~104 km2. Two novel methodologies to retrieve the landscape/regional carbon balance information captured by the CO2 concentration measurements are explored and compared in this study: boundary-layer budgeting and remote sensing-based footprint integration. We investigated four boreal continental sites in this study. Boundary-layer budgeting: By assuming the horizontal advection is negligible, the regional surface net flux (representative of an upwind area ~105 km2) can be calculated as, Fc=(Cm-CFT)ù+dC/dt*zi, where ù is the mean vertical velocity, zi is the mean ABL height, and and are the biweekly mean mixing ratio of CO2 in the ABL and the free troposphere, respectively. ù is from the NCEP (National Centers for Environmental Prediction) reanalysis data, while zi was simulated by an one-dimensional ABL model. The CO2 flux in the upwind area of the tower was also estimated based on ecosystem modeling using remote sensing measurements. Remote sensing-based footprint integration: The total regional flux captured by the sensor on a tower (mixing ratio) is the weighted sum of the upwind footprint source areas (Ømega), Fc= Σ FiWi, where Fi and Wi are the CO2 flux and its weighting factor for each pixel, respectively. Fiis calculated using an ecosystem model (BEPS: Boreal Ecosystem Productivity Simulator). Wiis comparative contribution factor of footprint function for each pixel within the whole footprint area as, Wi= fi/Σ fi, while the footprint function fi (the pixel i with x,y coordinates; x and y are along and the cross daily mean wind direction, respectively) is computed using a concentration footprint model as, fi(x,y,zm-z0)=Dy(x,y)Dz(x,zm)/U(x) Where Dy and Dz are the crosswind and vertical concentration distribution function, respectively and U(x) is the effective speed of plume advection. They are dependant on standard surface-layer scaling parameters and based on an analytical solution of Eulerian theory. Methodology comparison: The regional fluxes estimated using these two methods matched well. These regional net CO2 flux estimates were also comparable to local-scale measurements by eddy covariance techniques. The calculated upwind regional CO2 flux shows considerable seasonal and inter-annual variations. Annual regional flux was sensitive to air temperature in boreal regions and the temperature-sensitivities were region dependent. Larger fluxes are found in the warmer growing seasons and warmer years in the boreal forest regions.

Hybridized Kibble-Zurek scaling in the driven critical dynamics across an overlapping critical region

NASA Astrophysics Data System (ADS)

Zhai, Liang-Jun; Wang, Huai-Yu; Yin, Shuai

2018-04-01

The conventional Kibble-Zurek scaling describes the scaling behavior in the driven dynamics across a single critical region. In this paper, we study the driven dynamics across an overlapping critical region, in which a critical region (Region A) is overlaid by another critical region (Region B). We develop a hybridized Kibble-Zurek scaling (HKZS) to characterize the scaling behavior in the driven process. According to the HKZS, the driven dynamics in the overlapping region can be described by the critical theories for both Region A and Region B simultaneously. This results in a constraint on the scaling function in the overlapping critical region. We take the quantum Ising chain in an imaginary longitudinal field as an example. In this model, the critical region of the Yang-Lee edge singularity and the critical region of the ferromagnetic-paramagnetic phase transition overlap with each other. We numerically confirm the HKZS by simulating the driven dynamics in this overlapping critical region. The HKZSs in other models are also discussed.

Feature analysis and primary causes of pre-flood season "cumulative effect" of torrential rain over South China

NASA Astrophysics Data System (ADS)

Chu, Qu-cheng; Wang, Qi-guang; Qiao, Shao-bo; Feng, Guo-lin

2018-01-01

When persistent rainfall occurs frequently over South China, meso-scale and micro-scale synoptic systems persist and expand in space and time and eventually form meso-scale and long-scale weather processes. The accumulation of multiple torrential rain processes is defined as a "cumulative effect" of torrential rain (CETR) event. In this paper, daily reanalysis datasets collected by the National Centers for Environmental Prediction-Department of Energy (NCEP-DOE) during 1979-2014 are used to study the anomalous features and causes of heavy CETR events over South China. The results show that there is a significant difference in the spatial distribution of the heavy CETR events. Based on the center position of the CETR, the middle region displayed middle-region-heavy CETR events while the western region displayed west-region-heavy CETR events. El Niño events in the previous period (December, January, February, March (DJFM)) are major extra-forcing factors of middle-region-heavy CETR events, which is beneficial for the continuous, anomalous Philippine Sea anticyclone and strengthens the West Pacific Subtropical High (WPSH), extending it more westward than normal. The primary water vapor source for precipitation in middle-region-heavy CETR events is the Tropical Western Pacific Ocean. The major extra-forcing factor of a west-region-heavy CETR is the negative anomaly in the southern Tropical Indian Ocean (TIO) during the previous period (DJFM). This factor is beneficial for strengthening the cross-equatorial flow and westerly winds from the Bay of Bengal to the South China Sea (SCS) and early SCS summer monsoon onset. The primary water vapor source of precipitation in the west-region-heavy CETR is the southern TIO.

Regional Contingencies in the Relationship between Aboveground Biomass and Litter in the World’s Grasslands

PubMed Central

O’Halloran, Lydia R.; Borer, Elizabeth T.; Seabloom, Eric W.; MacDougall, Andrew S.; Cleland, Elsa E.; McCulley, Rebecca L.; Hobbie, Sarah; Harpole, W. Stan; DeCrappeo, Nicole M.; Chu, Chengjin; Bakker, Jonathan D.; Davies, Kendi F.; Du, Guozhen; Firn, Jennifer; Hagenah, Nicole; Hofmockel, Kirsten S.; Knops, Johannes M. H.; Li, Wei; Melbourne, Brett A.; Morgan, John W.; Orrock, John L.; Prober, Suzanne M.; Stevens, Carly J.

2013-01-01

Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a single vegetation type across multiple regions, obfuscating the drivers and generality of the association between production and decomposition. Furthermore, our understanding of the relationships between production and decomposition rests heavily on separate meta-analyses of each response, because no studies have simultaneously measured production and the accumulation or decomposition of litter using consistent methods at globally relevant scales. Here, we use a multi-country grassland dataset collected using a standardized protocol to show that live plant biomass (an estimate of aboveground net primary production) and litter disappearance (represented by mass loss of aboveground litter) do not strongly covary. Live biomass and litter disappearance varied at different spatial scales. There was substantial variation in live biomass among continents, sites and plots whereas among continent differences accounted for most of the variation in litter disappearance rates. Although there were strong associations among aboveground biomass, litter disappearance and climatic factors in some regions (e.g. U.S. Great Plains), these relationships were inconsistent within and among the regions represented by this study. These results highlight the importance of replication among regions and continents when characterizing the correlations between ecosystem processes and interpreting their global-scale implications for carbon flux. We must exercise caution in parameterizing litter decomposition and aboveground production in future regional and global carbon models as their relationship is complex. PMID:23405103

Eruptions that Drive Coronal Jets in a Solar Active Region

NASA Technical Reports Server (NTRS)

Sterling, Alphonse C.; Moore, Ronald L.; Falconer, David A.; Panesar, Navdeep K.; Akiyama, Sachiko; Yashiro, Seiji; Gopalswamy, Nat

2016-01-01

Solar coronal jets are common in both coronal holes and in active regions (e.g., Shibata et al. 1992, Shimojo et al. 1996, Cirtain et al. 2007. Savcheva et al. 2007). Recently, Sterling et al. (2015), using data from Hinode/XRT and SDO/AIA, found that coronal jets originating in polar coronal holes result from the eruption of small-scale filaments (minifilaments). The jet bright point (JBP) seen in X-rays and hotter EUV channels off to one side of the base of the jet's spire develops at the location where the minifilament erupts, consistent with the JBPs being miniature versions of typical solar flares that occur in the wake of large-scale filament eruptions. Here we consider whether active region coronal jets also result from the same minifilament-eruption mechanism, or whether they instead result from a different mechanism (e.g. Yokoyama & Shibata 1995). We present observations of an on-disk active region (NOAA AR 11513) that produced numerous jets on 2012 June 30, using data from SDO/AIA and HMI, and from GOES/SXI. We find that several of these active region jets also originate with eruptions of miniature filaments (size scale 20'') emanating from small-scale magnetic neutral lines of the region. This demonstrates that active region coronal jets are indeed frequently driven by minifilament eruptions. Other jets from the active region were also consistent with their drivers being minifilament eruptions, but we could not confirm this because the onsets of those jets were hidden from our view. This work was supported by funding from NASA/LWS, NASA/HGI, and Hinode. A full report of this study appears in Sterling et al. (2016).

Regional contingencies in the relationship between aboveground Bbomass and litter in the world’s grasslands

USGS Publications Warehouse

O’Halloran, Lydia R.; Borer, Elizabeth T.; Seabloom, Eric W.; MacDougall, Andrew S.; Cleland, Elsa E.; McCulley, Rebecca L.; Hobbie, Sarah; Harpole, W. Stan; DeCrappeo, Nicole M.; Chu, Cheng-Jin; Bakker, Jonathan D.; Davies, Kendi F.; Du, Guozhen; Firn, Jennifer; Hagenah, Nicole; Hofmockel, Kirsten S.; Knops, Johannes M.H.; Li, Wei; Melbourne, Brett A.; Morgan, John W.; Orrock, John L.; Prober, Suzanne M.; Stevens, Carly J.

2013-01-01

Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a single vegetation type across multiple regions, obfuscating the drivers and generality of the association between production and decomposition. Furthermore, our understanding of the relationships between production and decomposition rests heavily on separate meta-analyses of each response, because no studies have simultaneously measured production and the accumulation or decomposition of litter using consistent methods at globally relevant scales. Here, we use a multi-country grassland dataset collected using a standardized protocol to show that live plant biomass (an estimate of aboveground net primary production) and litter disappearance (represented by mass loss of aboveground litter) do not strongly covary. Live biomass and litter disappearance varied at different spatial scales. There was substantial variation in live biomass among continents, sites and plots whereas among continent differences accounted for most of the variation in litter disappearance rates. Although there were strong associations among aboveground biomass, litter disappearance and climatic factors in some regions (e.g. U.S. Great Plains), these relationships were inconsistent within and among the regions represented by this study. These results highlight the importance of replication among regions and continents when characterizing the correlations between ecosystem processes and interpreting their global-scale implications for carbon flux. We must exercise caution in parameterizing litter decomposition and aboveground production in future regional and global carbon models as their relationship is complex.

Estimating surface visibility at Hong Kong from ground-based LIDAR, sun photometer and operational MODIS products.

PubMed

Shahzad, Muhammad I; Nichol, Janet E; Wang, Jun; Campbell, James R; Chan, Pak W

2013-09-01

Hong Kong's surface visibility has decreased in recent years due to air pollution from rapid social and economic development in the region. In addition to deteriorating health standards, reduced visibility disrupts routine civil and public operations, most notably transportation and aviation. Regional estimates of visibility solved operationally using available ground and satellite-based estimates of aerosol optical properties and vertical distribution may prove more effective than standard reliance on a few existing surface visibility monitoring stations. Previous studies have demonstrated that such satellite measurements correlate well with near-surface optical properties, despite these sensors do not consider range-resolved information and indirect parameterizations necessary to solve relevant parameters. By expanding such analysis to include vertically resolved aerosol profile information from an autonomous ground-based lidar instrument, this work develops six models for automated assessment of surface visibility. Regional visibility is estimated using co-incident ground-based lidar, sun photometer visibility meter and MODerate-resolution maging Spectroradiometer (MODIS) aerosol optical depth data sets. Using a 355 nm extinction coefficient profile solved from the lidar MODIS AOD (aerosol optical depth) is scaled down to the surface to generate a regional composite depiction of surface visibility. These results demonstrate the potential for applying passive satellite depictions of broad-scale aerosol optical properties together with a ground-based surface lidar and zenith-viewing sun photometer for improving quantitative assessments of visibility in a city such as Hong Kong.

Regional crop yield forecasting: a probabilistic approach

NASA Astrophysics Data System (ADS)

de Wit, A.; van Diepen, K.; Boogaard, H.

2009-04-01

Information on the outlook on yield and production of crops over large regions is essential for government services dealing with import and export of food crops, for agencies with a role in food relief, for international organizations with a mandate in monitoring the world food production and trade, and for commodity traders. Process-based mechanistic crop models are an important tool for providing such information, because they can integrate the effect of crop management, weather and soil on crop growth. When properly integrated in a yield forecasting system, the aggregated model output can be used to predict crop yield and production at regional, national and continental scales. Nevertheless, given the scales at which these models operate, the results are subject to large uncertainties due to poorly known weather conditions and crop management. Current yield forecasting systems are generally deterministic in nature and provide no information about the uncertainty bounds on their output. To improve on this situation we present an ensemble-based approach where uncertainty bounds can be derived from the dispersion of results in the ensemble. The probabilistic information provided by this ensemble-based system can be used to quantify uncertainties (risk) on regional crop yield forecasts and can therefore be an important support to quantitative risk analysis in a decision making process.

Regional-Scale Climate Change: Observations and Model Simulations

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

Bradley, Raymond S; Diaz, Henry F

2010-12-14

This collaborative proposal addressed key issues in understanding the Earth's climate system, as highlighted by the U.S. Climate Science Program. The research focused on documenting past climatic changes and on assessing future climatic changes based on suites of global and regional climate models. Geographically, our emphasis was on the mountainous regions of the world, with a particular focus on the Neotropics of Central America and the Hawaiian Islands. Mountain regions are zones where large variations in ecosystems occur due to the strong climate zonation forced by the topography. These areas are particularly susceptible to changes in critical ecological thresholds, andmore » we conducted studies of changes in phonological indicators based on various climatic thresholds.« less

Estimating missing hourly climatic data using artificial neural network for energy balance based ET mapping applications

USDA-ARS?s Scientific Manuscript database

Remote sensing based evapotranspiration (ET) mapping has become an important tool for water resources management at a regional scale. Accurate hourly climatic data and reference ET are crucial input for successfully implementing remote sensing based ET models such as Mapping ET with internal calibra...

Process-based principles for restoring river ecosystems

Treesearch

Timothy J. Beechie; David A. Sear; Julian D. Olden; George R. Pess; John M. Buffington; Hamish Moir; Philip Roni; Michael M. Pollock

2010-01-01

Process-based restoration aims to reestablish normative rates and magnitudes of physical, chemical, and biological processes that sustain river and floodplain ecosystems. Ecosystem conditions at any site are governed by hierarchical regional, watershed, and reach-scale processes controlling hydrologic and sediment regimes; floodplain and aquatic habitat...

Mechanisms Responsible for the Observed Thermodynamic Structure in a Convective Boundary Layer Over the Hudson Valley of New York State

NASA Astrophysics Data System (ADS)

Freedman, Jeffrey M.; Fitzjarrald, David R.

2017-02-01

We examine cases of a regional elevated mixed layer (EML) observed during the Hudson Valley Ambient Meteorology Study (HVAMS) conducted in New York State, USA in 2003. Previously observed EMLs referred to topographic domains on scales of 105 -106 km2 . Here, we present observational evidence of the mechanisms responsible for the development and maintenance of regional EMLs overlying a valley-based convective boundary layer (CBL) on much smaller spatial scales (<5000 km2) . Using observations from aircraft-based, balloon-based, and surface-based platforms deployed during the HVAMS, we show that cross-valley horizontal advection, along-valley channelling, and fog-induced cold-air pooling are responsible for the formation and maintenance of the EML and valley-CBL coupling over New York State's Hudson Valley. The upper layer stability of the overlying EML constrains growth of the valley CBL, and this has important implications for air dispersion, aviation interests, and fog forecasting.

Vertical land motion controls regional sea level rise patterns on the United States east coast since 1900

NASA Astrophysics Data System (ADS)

Piecuch, C. G.; Huybers, P. J.; Hay, C.; Mitrovica, J. X.; Little, C. M.; Ponte, R. M.; Tingley, M.

2017-12-01

Understanding observed spatial variations in centennial relative sea level trends on the United States east coast has important scientific and societal applications. Past studies based on models and proxies variously suggest roles for crustal displacement, ocean dynamics, and melting of the Greenland ice sheet. Here we perform joint Bayesian inference on regional relative sea level, vertical land motion, and absolute sea level fields based on tide gauge records and GPS data. Posterior solutions show that regional vertical land motion explains most (80% median estimate) of the spatial variance in the large-scale relative sea level trend field on the east coast over 1900-2016. The posterior estimate for coastal absolute sea level rise is remarkably spatially uniform compared to previous studies, with a spatial average of 1.4-2.3 mm/yr (95% credible interval). Results corroborate glacial isostatic adjustment models and reveal that meaningful long-period, large-scale vertical velocity signals can be extracted from short GPS records.

Image Patch Analysis of Sunspots and Active Regions

NASA Astrophysics Data System (ADS)

Moon, K.; Delouille, V.; Hero, A.

2017-12-01

The flare productivity of an active region has been observed to be related to its spatial complexity. Separating active regions that are quiet from potentially eruptive ones is a key issue in space weather applications. Traditional classification schemes such as Mount Wilson and McIntosh have been effective in relating an active region large scale magnetic configuration to its ability to produce eruptive events. However, their qualitative nature does not use all of the information present in the observations. In our work, we present an image patch analysis for characterizing sunspots and active regions. We first propose fine-scale quantitative descriptors for an active region's complexity such as intrinsic dimension, and we relate them to the Mount Wilson classification. Second, we introduce a new clustering of active regions that is based on the local geometry observed in Line of Sight magnetogram and continuum images. To obtain this local geometry, we use a reduced-dimension representation of an active region that is obtained by factoring the corresponding data matrix comprised of local image patches using the singular value decomposition. The resulting factorizations of active regions can be compared via the definition of appropriate metrics on the factors. The distances obtained from these metrics are then used to cluster the active regions. Results. We find that these metrics result in natural clusterings of active regions. The clusterings are related to large scale descriptors of an active region such as its size, its local magnetic field distribution, and its complexity as measured by the Mount Wilson classification scheme. We also find that including data focused on the neutral line of an active region can result in an increased correspondence between our clustering results and other active region descriptors such as the Mount Wilson classifications and the R-value.

Effects of forcing time scale on the simulated turbulent flows and turbulent collision statistics of inertial particles

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

Rosa, B., E-mail: bogdan.rosa@imgw.pl; Parishani, H.; Department of Earth System Science, University of California, Irvine, California 92697-3100

2015-01-15

In this paper, we study systematically the effects of forcing time scale in the large-scale stochastic forcing scheme of Eswaran and Pope [“An examination of forcing in direct numerical simulations of turbulence,” Comput. Fluids 16, 257 (1988)] on the simulated flow structures and statistics of forced turbulence. Using direct numerical simulations, we find that the forcing time scale affects the flow dissipation rate and flow Reynolds number. Other flow statistics can be predicted using the altered flow dissipation rate and flow Reynolds number, except when the forcing time scale is made unrealistically large to yield a Taylor microscale flow Reynoldsmore » number of 30 and less. We then study the effects of forcing time scale on the kinematic collision statistics of inertial particles. We show that the radial distribution function and the radial relative velocity may depend on the forcing time scale when it becomes comparable to the eddy turnover time. This dependence, however, can be largely explained in terms of altered flow Reynolds number and the changing range of flow length scales present in the turbulent flow. We argue that removing this dependence is important when studying the Reynolds number dependence of the turbulent collision statistics. The results are also compared to those based on a deterministic forcing scheme to better understand the role of large-scale forcing, relative to that of the small-scale turbulence, on turbulent collision of inertial particles. To further elucidate the correlation between the altered flow structures and dynamics of inertial particles, a conditional analysis has been performed, showing that the regions of higher collision rate of inertial particles are well correlated with the regions of lower vorticity. Regions of higher concentration of pairs at contact are found to be highly correlated with the region of high energy dissipation rate.« less

A multi-scale comparison of trait linkages to environmental and spatial variables in fish communities across a large freshwater lake.

PubMed

Strecker, Angela L; Casselman, John M; Fortin, Marie-Josée; Jackson, Donald A; Ridgway, Mark S; Abrams, Peter A; Shuter, Brian J

2011-07-01

Species present in communities are affected by the prevailing environmental conditions, and the traits that these species display may be sensitive indicators of community responses to environmental change. However, interpretation of community responses may be confounded by environmental variation at different spatial scales. Using a hierarchical approach, we assessed the spatial and temporal variation of traits in coastal fish communities in Lake Huron over a 5-year time period (2001-2005) in response to biotic and abiotic environmental factors. The association of environmental and spatial variables with trophic, life-history, and thermal traits at two spatial scales (regional basin-scale, local site-scale) was quantified using multivariate statistics and variation partitioning. We defined these two scales (regional, local) on which to measure variation and then applied this measurement framework identically in all 5 study years. With this framework, we found that there was no change in the spatial scales of fish community traits over the course of the study, although there were small inter-annual shifts in the importance of regional basin- and local site-scale variables in determining community trait composition (e.g., life-history, trophic, and thermal). The overriding effects of regional-scale variables may be related to inter-annual variation in average summer temperature. Additionally, drivers of fish community traits were highly variable among study years, with some years dominated by environmental variation and others dominated by spatially structured variation. The influence of spatial factors on trait composition was dynamic, which suggests that spatial patterns in fish communities over large landscapes are transient. Air temperature and vegetation were significant variables in most years, underscoring the importance of future climate change and shoreline development as drivers of fish community structure. Overall, a trait-based hierarchical framework may be a useful conservation tool, as it highlights the multi-scaled interactive effect of variables over a large landscape.

Soil Functional Mapping: A Geospatial Framework for Scaling Soil Carbon Cycling

NASA Astrophysics Data System (ADS)

Lawrence, C. R.

2017-12-01

Climate change is dramatically altering biogeochemical cycles in most terrestrial ecosystems, particularly the cycles of water and carbon (C). These changes will affect myriad ecosystem processes of importance, including plant productivity, C exports to aquatic systems, and terrestrial C storage. Soil C storage represents a critical feedback to climate change as soils store more C than the atmosphere and aboveground plant biomass combined. While we know plant and soil C cycling are strongly coupled with soil moisture, substantial unknowns remain regarding how these relationships can be scaled up from soil profiles to ecosystems. This greatly limits our ability to build a process-based understanding of the controls on and consequences of climate change at regional scales. In an effort to address this limitation we: (1) describe an approach to classifying soils that is based on underlying differences in soil functional characteristics and (2) examine the utility of this approach as a scaling tool that honors the underlying soil processes. First, geospatial datasets are analyzed in the context of our current understanding of soil C and water cycling in order to predict soil functional units that can be mapped at the scale of ecosystems or watersheds. Next, the integrity of each soil functional unit is evaluated using available soil C data and mapping units are refined as needed. Finally, targeted sampling is conducted to further differentiate functional units or fill in any data gaps that are identified. Completion of this workflow provides new geospatial datasets that are based on specific soil functions, in this case the coupling of soil C and water cycling, and are well suited for integration with regional-scale soil models. Preliminary results from this effort highlight the advantages of a scaling approach that balances theory, measurement, and modeling.

The high-resolution regional reanalysis COSMO-REA6

NASA Astrophysics Data System (ADS)

Ohlwein, C.

2016-12-01

Reanalyses gain more and more importance as a source of meteorological information for many purposes and applications. Several global reanalyses projects (e.g., ERA, MERRA, CSFR, JMA9) produce and verify these data sets to provide time series as long as possible combined with a high data quality. Due to a spatial resolution down to 50-70km and 3-hourly temporal output, they are not suitable for small scale problems (e.g., regional climate assessment, meso-scale NWP verification, input for subsequent models such as river runoff simulations). The implementation of regional reanalyses based on a limited area model along with a data assimilation scheme is able to generate reanalysis data sets with high spatio-temporal resolution. Within the Hans-Ertel-Centre for Weather Research (HErZ), the climate monitoring branch concentrates efforts on the assessment and analysis of regional climate in Germany and Europe. In joint cooperation with DWD (German Meteorological Service), a high-resolution reanalysis system based on the COSMO model has been developed. The regional reanalysis for Europe matches the domain of the CORDEX EURO-11 specifications, albeit at a higher spatial resolution, i.e., 0.055° (6km) instead of 0.11° (12km) and comprises the assimilation of observational data using the existing nudging scheme of COSMO complemented by a special soil moisture analysis with boundary conditions provided by ERA-Interim data. The reanalysis data set covers the past 20 years. Extensive evaluation of the reanalysis is performed using independent observations with special emphasis on precipitation and high-impact weather situations indicating a better representation of small scale variability. Further, the evaluation shows an added value of the regional reanalysis with respect to the forcing ERA Interim reanalysis and compared to a pure high-resolution dynamical downscaling approach without data assimilation.

A high-resolution regional reanalysis for Europe

NASA Astrophysics Data System (ADS)

Ohlwein, C.

2015-12-01

Reanalyses gain more and more importance as a source of meteorological information for many purposes and applications. Several global reanalyses projects (e.g., ERA, MERRA, CSFR, JMA9) produce and verify these data sets to provide time series as long as possible combined with a high data quality. Due to a spatial resolution down to 50-70km and 3-hourly temporal output, they are not suitable for small scale problems (e.g., regional climate assessment, meso-scale NWP verification, input for subsequent models such as river runoff simulations). The implementation of regional reanalyses based on a limited area model along with a data assimilation scheme is able to generate reanalysis data sets with high spatio-temporal resolution. Within the Hans-Ertel-Centre for Weather Research (HErZ), the climate monitoring branch concentrates efforts on the assessment and analysis of regional climate in Germany and Europe. In joint cooperation with DWD (German Meteorological Service), a high-resolution reanalysis system based on the COSMO model has been developed. The regional reanalysis for Europe matches the domain of the CORDEX EURO-11 specifications, albeit at a higher spatial resolution, i.e., 0.055° (6km) instead of 0.11° (12km) and comprises the assimilation of observational data using the existing nudging scheme of COSMO complemented by a special soil moisture analysis with boundary conditions provided by ERA-Interim data. The reanalysis data set covers the past 20 years. Extensive evaluation of the reanalysis is performed using independent observations with special emphasis on precipitation and high-impact weather situations indicating a better representation of small scale variability. Further, the evaluation shows an added value of the regional reanalysis with respect to the forcing ERA Interim reanalysis and compared to a pure high-resolution dynamical downscaling approach without data assimilation.

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis

PubMed Central

Gobiet, Andreas

2016-01-01

ABSTRACT Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio‐temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan‐European data sets and a set that combines eight very high‐resolution station‐based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post‐processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small‐scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate‐mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments. PMID:28111497

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis.

PubMed

Prein, Andreas F; Gobiet, Andreas

2017-01-01

Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio-temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan-European data sets and a set that combines eight very high-resolution station-based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post-processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small-scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate-mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments.

Climate fails to predict wood decomposition at regional scales

NASA Astrophysics Data System (ADS)

Bradford, Mark A.; Warren, Robert J., II; Baldrian, Petr; Crowther, Thomas W.; Maynard, Daniel S.; Oldfield, Emily E.; Wieder, William R.; Wood, Stephen A.; King, Joshua R.

2014-07-01

Decomposition of organic matter strongly influences ecosystem carbon storage. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on mean responses can be irrelevant and misleading. We test whether climate controls on the decomposition rate of dead wood--a carbon stock estimated to represent 73 +/- 6 Pg carbon globally--are sensitive to the spatial scale from which they are inferred. We show that the common assumption that climate is a predominant control on decomposition is supported only when local-scale variation is aggregated into mean values. Disaggregated data instead reveal that local-scale factors explain 73% of the variation in wood decomposition, and climate only 28%. Further, the temperature sensitivity of decomposition estimated from local versus mean analyses is 1.3-times greater. Fundamental issues with mean correlations were highlighted decades ago, yet mean climate-decomposition relationships are used to generate simulations that inform management and adaptation under environmental change. Our results suggest that to predict accurately how decomposition will respond to climate change, models must account for local-scale factors that control regional dynamics.

A multi-year estimate of methane fluxes in Alaska from CARVE atmospheric observations

PubMed Central

Miller, Scot M.; Miller, Charles E.; Commane, Roisin; Chang, Rachel Y.-W.; Dinardo, Steven J.; Henderson, John M.; Karion, Anna; Lindaas, Jakob; Melton, Joe R.; Miller, John B.; Sweeney, Colm; Wofsy, Steven C.; Michalak, Anna M.

2016-01-01

Methane (CH4) fluxes from Alaska and other arctic regions may be sensitive to thawing permafrost and future climate change, but estimates of both current and future fluxes from the region are uncertain. This study estimates CH4 fluxes across Alaska for 2012–2014 using aircraft observations from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) and a geostatistical inverse model (GIM). We find that a simple flux model based on a daily soil temperature map and a static map of wetland extent reproduces the atmospheric CH4 observations at the state-wide, multi-year scale more effectively than global-scale, state-of-the-art process-based models. This result points to a simple and effective way of representing CH4 flux patterns across Alaska. It further suggests that contemporary process-based models can improve their representation of key processes that control fluxes at regional scales, and that more complex processes included in these models cannot be evaluated given the information content of available atmospheric CH4 observations. In addition, we find that CH4 emissions from the North Slope of Alaska account for 24% of the total statewide flux of 1.74 ± 0.44 Tg CH4 (for May–Oct.). Contemporary global-scale process models only attribute an average of 3% of the total flux to this region. This mismatch occurs for two reasons: process models likely underestimate wetland area in regions without visible surface water, and these models prematurely shut down CH4 fluxes at soil temperatures near 0°C. As a consequence, wetlands covered by vegetation and wetlands with persistently cold soils could be larger contributors to natural CH4 fluxes than in process estimates. Lastly, we find that the seasonality of CH4 fluxes varied during 2012–2014, but that total emissions did not differ significantly among years, despite substantial differences in soil temperature and precipitation; year-to-year variability in these environmental conditions did not affect obvious changes in total CH4 fluxes from the state. PMID:28066129

A multi-year estimate of methane fluxes in Alaska from CARVE atmospheric observations.

PubMed

Miller, Scot M; Miller, Charles E; Commane, Roisin; Chang, Rachel Y-W; Dinardo, Steven J; Henderson, John M; Karion, Anna; Lindaas, Jakob; Melton, Joe R; Miller, John B; Sweeney, Colm; Wofsy, Steven C; Michalak, Anna M

2016-10-01

Methane (CH 4 ) fluxes from Alaska and other arctic regions may be sensitive to thawing permafrost and future climate change, but estimates of both current and future fluxes from the region are uncertain. This study estimates CH 4 fluxes across Alaska for 2012-2014 using aircraft observations from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) and a geostatistical inverse model (GIM). We find that a simple flux model based on a daily soil temperature map and a static map of wetland extent reproduces the atmospheric CH 4 observations at the state-wide, multi-year scale more effectively than global-scale, state-of-the-art process-based models. This result points to a simple and effective way of representing CH 4 flux patterns across Alaska. It further suggests that contemporary process-based models can improve their representation of key processes that control fluxes at regional scales, and that more complex processes included in these models cannot be evaluated given the information content of available atmospheric CH 4 observations. In addition, we find that CH 4 emissions from the North Slope of Alaska account for 24% of the total statewide flux of 1.74 ± 0.44 Tg CH 4 ( for May-Oct.). Contemporary global-scale process models only attribute an average of 3% of the total flux to this region. This mismatch occurs for two reasons: process models likely underestimate wetland area in regions without visible surface water, and these models prematurely shut down CH 4 fluxes at soil temperatures near 0°C. As a consequence, wetlands covered by vegetation and wetlands with persistently cold soils could be larger contributors to natural CH 4 fluxes than in process estimates. Lastly, we find that the seasonality of CH 4 fluxes varied during 2012-2014, but that total emissions did not differ significantly among years, despite substantial differences in soil temperature and precipitation; year-to-year variability in these environmental conditions did not affect obvious changes in total CH 4 fluxes from the state.

A medium-scale traveling ionospheric disturbance observed from the ground and from space

NASA Astrophysics Data System (ADS)

Dymond, K. F.; Watts, C.; Coker, C.; Budzien, S. A.; Bernhardt, P. A.; Kassim, N.; Lazio, T. J.; Weiler, K.; Crane, P. C.; Ray, P. S.; Cohen, A.; Clarke, T.; Rickard, L. J.; Taylor, G. B.; Schinzel, F.; Pihlstrom, Y.; Kuniyoshi, M.; Close, S.; Colestock, P.; Myers, S.; Datta, A.

2011-10-01

We report ultraviolet optical observations from space of a Medium-Scale Traveling Ionospheric Disturbance (MSTID) made during the Combined Radio Interferometry and COSMIC Experiment in Tomography Campaign (CRICKET) held on September 15, 2007 at ˜8:30 UT. The experiment used a Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC also known as FORMOSAT-3) satellite in conjunction with the Very Large Array (VLA) radio telescope, located near Socorro, NM, to study the ionosphere from the global scale down to the regional scale while the TIDs propagated through it. The COSMIC/FORMOSAT-3 satellite measured the F region electron density both horizontally and with altitude while the VLA measured the directions and speeds of the TIDs. These observations provide new information on this poorly understood class of TID and demonstrate the possibility of studying MSTIDs using space-based optical instruments.

Mechanisms of plant survival and mortality during drought: Why do some plants survive while others succumb to drought?

Treesearch

Nate McDowell; William T. Pockman; Craig D. Allen; David D. Breshears; Neil Cobb; Thomas Kolb; Jennifer Plaut; John Sperry; Adam West; David G. Williams; Enrico A. Yepez

2008-01-01

Severe droughts have been associated with regional-scale forest mortality worldwide. Climate change is expected to exacerbate regional mortality events; however, prediction remains difficult because the physiological mechanisms underlying drought survival and mortality are poorly understood. We developed a hydraulically based theory considering carbon balance and...

AgMIP Coordinated Global and Regional Assessments for 1.5°C and 2.0°C

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2017-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study performs a proof-of-concept of the CGRA to demonstrate advantages and challenges of the framework. This effort responds to the request by UNFCCC for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), HAPPI and CMIP5 ensemble scenarios, global gridded crop models, global agricultural economic models, site-based crop models, and within-country regional economic models. CGRA results show that at the global scale, mixed areas of positive and negative simulated yield changes, with declines in some breadbasket regions led to overall declines in productivity at both 1.5°C and 2.0°C. These projected global yield changes resulted in increases in prices of major commodities in a global economic model. Simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on region and crop, but with more negative effects on productivity at 2.0°C than at 1.5°C for the most part. In conjunction with price changes from the global economics models, these productivity declines resulted generally in small positive effects on regional farm livelihoods, showing that farming systems should continue to be viable under high mitigation scenarios. CGRA protocols focus on how mitigation actions and effects differ across scales, with main mechanisms studied in the integrated assessment models being policies and technologies that reduce direct non-CO2 emissions from agriculture, reduce CO2 emissions from land use change and forest sink enhancement, and utilize biomass for energy production. At regional scales, increasing soil organic carbon (SOC) is of active interest.

Some issues related to the novel spectral acceleration method for the fast computation of radiation/scattering from one-dimensional extremely large scale quasi-planar structures

NASA Astrophysics Data System (ADS)

Torrungrueng, Danai; Johnson, Joel T.; Chou, Hsi-Tseng

2002-03-01

The novel spectral acceleration (NSA) algorithm has been shown to produce an $[\\mathcal{O}]$(Ntot) efficient iterative method of moments for the computation of radiation/scattering from both one-dimensional (1-D) and two-dimensional large-scale quasi-planar structures, where Ntot is the total number of unknowns to be solved. This method accelerates the matrix-vector multiplication in an iterative method of moments solution and divides contributions between points into ``strong'' (exact matrix elements) and ``weak'' (NSA algorithm) regions. The NSA method is based on a spectral representation of the electromagnetic Green's function and appropriate contour deformation, resulting in a fast multipole-like formulation in which contributions from large numbers of points to a single point are evaluated simultaneously. In the standard NSA algorithm the NSA parameters are derived on the basis of the assumption that the outermost possible saddle point, φs,max, along the real axis in the complex angular domain is small. For given height variations of quasi-planar structures, this assumption can be satisfied by adjusting the size of the strong region Ls. However, for quasi-planar structures with large height variations, the adjusted size of the strong region is typically large, resulting in significant increases in computational time for the computation of the strong-region contribution and degrading overall efficiency of the NSA algorithm. In addition, for the case of extremely large scale structures, studies based on the physical optics approximation and a flat surface assumption show that the given NSA parameters in the standard NSA algorithm may yield inaccurate results. In this paper, analytical formulas associated with the NSA parameters for an arbitrary value of φs,max are presented, resulting in more flexibility in selecting Ls to compromise between the computation of the contributions of the strong and weak regions. In addition, a ``multilevel'' algorithm, decomposing 1-D extremely large scale quasi-planar structures into more than one weak region and appropriately choosing the NSA parameters for each weak region, is incorporated into the original NSA method to improve its accuracy.

Re-plumbing the Terrestrial Hydrosphere: Scope and Impact of Major Inter-basin Water Transfers

NASA Astrophysics Data System (ADS)

Shikhmacheva, K. V.; Vorosmarty, C. J.; Fekete, B. M.; Afshari, S.; Aside, B.; Chibisova, Y.; Dopson, I.; Link, H.; Mouden, A.

2013-12-01

The availability of water has become one of the main concerns in modern history and it is an important policymaking strategy. Increasing population, agricultural intensification, rapid urbanization, industrial expansion and environmental changes increase water demand on region and global scales. Inter-Basin Water Transfer (IBWT) is an important element of satisfying immediate water requirements. The complex engineering structures divert water flow between watersheds, thus ';re-plumbing' terrestrial hydrosphere. We report here an analysis of inter-basin water transfer for the Northeast region, which is a part of an NSF funded project entitled 'The NorthEast Regional Earth System Model (NE-RESM).' In addition, this work is also a part of a global IBWT study. First, we present the IBWT geo-referenced assembled data set, derived from from maps, published documents and online resources. The information in the data base was classified by project name, diverted volume, source location, usage, status of construction, transport distance and purpose. The key feature of the dataset is geo-location of the projects, that allows further analysis of the hydrologic impact of each of the projects as well as their collective significance. Upon completion of the data-collection phase, the inputs were verified using RiverGIS and ArcGIS software. In addition, we investigated some key measures of IBWT distortion of regional-scale hydrology as well as their socio-economic impacts across the Northeast region. We calculated several indicators to assess these impacts, for example the donor-to-recipient basin flow ratio, which represents the 'gain' and 'loss' of water relative to the natural flow on a basin scale. Elements of the regional IBWT data base will be incorporated into the regional-scale Water Balance Model (WBM), and linked to the operation of reservoirs and dams. While focused on the Northeastern U.S., we believe that this data, its testing and applications will yield broad use and interest across the community, giving researchers a next important resource in the arsenal of datasets depicting human-water interactions.

Multiple-length-scale deformation analysis in a thermoplastic polyurethane

PubMed Central

Sui, Tan; Baimpas, Nikolaos; Dolbnya, Igor P.; Prisacariu, Cristina; Korsunsky, Alexander M.

2015-01-01

Thermoplastic polyurethane elastomers enjoy an exceptionally wide range of applications due to their remarkable versatility. These block co-polymers are used here as an example of a structurally inhomogeneous composite containing nano-scale gradients, whose internal strain differs depending on the length scale of consideration. Here we present a combined experimental and modelling approach to the hierarchical characterization of block co-polymer deformation. Synchrotron-based small- and wide-angle X-ray scattering and radiography are used for strain evaluation across the scales. Transmission electron microscopy image-based finite element modelling and fast Fourier transform analysis are used to develop a multi-phase numerical model that achieves agreement with the combined experimental data using a minimal number of adjustable structural parameters. The results highlight the importance of fuzzy interfaces, that is, regions of nanometre-scale structure and property gradients, in determining the mechanical properties of hierarchical composites across the scales. PMID:25758945

Stable functional networks exhibit consistent timing in the human brain.

PubMed

Chapeton, Julio I; Inati, Sara K; Zaghloul, Kareem A

2017-03-01

Despite many advances in the study of large-scale human functional networks, the question of timing, stability, and direction of communication between cortical regions has not been fully addressed. At the cellular level, neuronal communication occurs through axons and dendrites, and the time required for such communication is well defined and preserved. At larger spatial scales, however, the relationship between timing, direction, and communication between brain regions is less clear. Here, we use a measure of effective connectivity to identify connections between brain regions that exhibit communication with consistent timing. We hypothesized that if two brain regions are communicating, then knowledge of the activity in one region should allow an external observer to better predict activity in the other region, and that such communication involves a consistent time delay. We examine this question using intracranial electroencephalography captured from nine human participants with medically refractory epilepsy. We use a coupling measure based on time-lagged mutual information to identify effective connections between brain regions that exhibit a statistically significant increase in average mutual information at a consistent time delay. These identified connections result in sparse, directed functional networks that are stable over minutes, hours, and days. Notably, the time delays associated with these connections are also highly preserved over multiple time scales. We characterize the anatomic locations of these connections, and find that the propagation of activity exhibits a preferred posterior to anterior temporal lobe direction, consistent across participants. Moreover, networks constructed from connections that reliably exhibit consistent timing between anatomic regions demonstrate features of a small-world architecture, with many reliable connections between anatomically neighbouring regions and few long range connections. Together, our results demonstrate that cortical regions exhibit functional relationships with well-defined and consistent timing, and the stability of these relationships over multiple time scales suggests that these stable pathways may be reliably and repeatedly used for large-scale cortical communication. Published by Oxford University Press on behalf of the Guarantors of Brain 2017. This work is written by US Government employees and is in the public domain in the United States.

Using Imaging Spectrometry measurements of Ecosystem Composition to constrain Regional Predictions of Carbon, Water and Energy Fluxes

NASA Astrophysics Data System (ADS)

Anderson, C.; Bond-Lamberty, B. P.; Huang, M.; Xu, Y.; Stegen, J.

2016-12-01

Ecosystem composition is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. The description of current ecosystem composition has traditionally come from relatively few ground-based inventories of the plant canopy, but are spatially limited and do not provide a comprehensive picture of ecosystem composition at regional or global scales. In this analysis, imaging spectrometry measurements, collected as part of the HyspIRI Preparatory Mission, are used to provide spatially-resolved estimates of plant functional type composition providing an important constraint on terrestrial biosphere model predictions of carbon, water and energy fluxes across the heterogeneous landscapes of the Californian Sierras. These landscapes include oak savannas, mid-elevation mixed pines, fir-cedar forests, and high elevation pines. Our results show that imaging spectrometry measurements can be successfully used to estimate regional-scale variation in ecosystem composition and resulting spatial heterogeneity in patterns of carbon, water and energy fluxes and ecosystem dynamics. Simulations at four flux tower sites within the study region yield patterns of seasonal and inter-annual variation in carbon and water fluxes that have comparable accuracy to simulations initialized from ground-based inventory measurements. Finally, results indicate that during the 2012-2015 Californian drought, regional net carbon fluxes fell by 84%, evaporation and transpiration fluxes fell by 53% and 33% respectively, and sensible heat increase by 51%. This study provides a framework for assimilating near-future global satellite imagery estimates of ecosystem composition with terrestrial biosphere models, constraining and improving their predictions of large-scale ecosystem dynamics and functioning.

Using Imaging Spectrometry measurements of Ecosystem Composition to constrain Regional Predictions of Carbon, Water and Energy Fluxes

NASA Astrophysics Data System (ADS)

Antonarakis, A. S.; Bogan, S.; Moorcroft, P. R.

2017-12-01

Ecosystem composition is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. The description of current ecosystem composition has traditionally come from relatively few ground-based inventories of the plant canopy, but are spatially limited and do not provide a comprehensive picture of ecosystem composition at regional or global scales. In this analysis, imaging spectrometry measurements, collected as part of the HyspIRI Preparatory Mission, are used to provide spatially-resolved estimates of plant functional type composition providing an important constraint on terrestrial biosphere model predictions of carbon, water and energy fluxes across the heterogeneous landscapes of the Californian Sierras. These landscapes include oak savannas, mid-elevation mixed pines, fir-cedar forests, and high elevation pines. Our results show that imaging spectrometry measurements can be successfully used to estimate regional-scale variation in ecosystem composition and resulting spatial heterogeneity in patterns of carbon, water and energy fluxes and ecosystem dynamics. Simulations at four flux tower sites within the study region yield patterns of seasonal and inter-annual variation in carbon and water fluxes that have comparable accuracy to simulations initialized from ground-based inventory measurements. Finally, results indicate that during the 2012-2015 Californian drought, regional net carbon fluxes fell by 84%, evaporation and transpiration fluxes fell by 53% and 33% respectively, and sensible heat increase by 51%. This study provides a framework for assimilating near-future global satellite imagery estimates of ecosystem composition with terrestrial biosphere models, constraining and improving their predictions of large-scale ecosystem dynamics and functioning.

Diagnosing isopycnal diffusivity in an eddying, idealized midlatitude ocean basin via Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT)

DOE PAGES

Wolfram, Phillip J.; Ringler, Todd D.; Maltrud, Mathew E.; ...

2015-08-01

Isopycnal diffusivity due to stirring by mesoscale eddies in an idealized, wind-forced, eddying, midlatitude ocean basin is computed using Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT). Simulation is performed via LIGHT within the Model for Prediction across Scales Ocean (MPAS-O). Simulations are performed at 4-, 8-, 16-, and 32-km resolution, where the first Rossby radius of deformation (RRD) is approximately 30 km. Scalar and tensor diffusivities are estimated at each resolution based on 30 ensemble members using particle cluster statistics. Each ensemble member is composed of 303 665 particles distributed across five potential density surfaces. Diffusivity dependence upon modelmore » resolution, velocity spatial scale, and buoyancy surface is quantified and compared with mixing length theory. The spatial structure of diffusivity ranges over approximately two orders of magnitude with values of O(10 5) m 2 s –1 in the region of western boundary current separation to O(10 3) m 2 s –1 in the eastern region of the basin. Dominant mixing occurs at scales twice the size of the first RRD. Model resolution at scales finer than the RRD is necessary to obtain sufficient model fidelity at scales between one and four RRD to accurately represent mixing. Mixing length scaling with eddy kinetic energy and the Lagrangian time scale yield mixing efficiencies that typically range between 0.4 and 0.8. In conclusion, a reduced mixing length in the eastern region of the domain relative to the west suggests there are different mixing regimes outside the baroclinic jet region.« less

Magnetic anomaly map of the central Cayman Trough, northwestern Caribbean Sea

USGS Publications Warehouse

Dillon, William P.; Edgar, N. Terence; Parson, Lindsay M.; Scanlon, Kathryn M.; Driscoll, George R.; Jacobs, Colin L.

1993-01-01

This is the first large-scale published map of magnetic anomalies in the central Cayman Trough area. Two previously published very small scale maps based on much less data are a regional map (Gough and Heirtzler, 1969) and a map compiled from several tracklines running parallel to the axis of the Cayman Trough (MacDonald and Holcombe, 1978).

A novel land surface-hydrologic-sediment dynamics model for stream corridor conservation assessment and its first application

NASA Astrophysics Data System (ADS)

Smithgall, K.; Shen, C.; Langendoen, E. J.; Johnson, P. A.

2015-12-01

Nationally and in the Chesapeake Bay (CB), Stream Corridor restoration costs unsustainable amount of public resources, but decisions are often made with inadequate knowledge of regional-scale system behavior. Bank erosion is a significant issue relevant to sediment and nutrient pollution, aquatic and riparian habitat and stream health. Existing modeling effort either focuses only on reach-scale responses or overly simplifies the descriptions for bank failure mechanics. In this work we present a novel regional-scale processes model integrating hydrology, vegetation dynamics, hydraulics, bank mechanics and sediment transport, based on a coupling between Community Land Model, Process-based Adaptive Watershed Simulator and CONservational Channel Evolution and Pollutant Transport System (CLM + PAWS + CONCEPTS, CPC). We illustrate the feasibility of this modeling platform in a Valley and Ridge basin in Pennsylvania, USA, with channel geometry data collected in 2004 and 2014. The simulations are able to reproduce essential pattern of the observed trends. We study the causes of the noticeable evolution of a relocated channel and the hydrologic controls. Bridging processes on multiple scales, the CPC model creates a new, integrated system that may serve as a confluence point for inter-disciplinary research.

High-latitude E Region Ionosphere-thermosphere Coupling: A Comparative Study Using in Situ and Incoherent Scatter Radar Observations

NASA Technical Reports Server (NTRS)

Burchill, J. K.; Clemmons, J. H.; Knudsen, D. J.; Larsen, M.; Nicolls, M. J.; Pfaff, R. F.; Rowland, D.; Sangalli, L.

2012-01-01

We present in situ and ground-based measurements of the ratio k of ion cyclotronangular frequency to ion-neutral momentum transfer collision frequency to investigateionosphere-thermosphere (IT) coupling in the auroral E region. In situ observations were obtained by NASA sounding rocket 36.234, which was launched into the nightsideE region ionosphere at 1229 UT on 19 January 2007 from Poker Flat, AK. The payload carried instrumentation to determine ion drift angle and electric field vectors. Neutral winds were measured by triangulating a chemical tracer released from rocket 41.064 launched two minutes later. k is calculated from the rotation of the ion drift angle relative to the E-cross-B drift direction in a frame co-rotating with the payload. Between the altitudes of 118 km and 130 km k increases exponentially with a scale height of 9.3 +/- 0.7 km, deviating from an exponential above 130 km. k = 1 at an altitude z(sub0) of 119.9 +/- 0.5 km. The ratio was also estimated from Poker Flat Incoherent Scatter Radar (PFISR) measurements using the rotation of ion velocity with altitude. Exponential fits to the PFISR measurements made during the flight of 41.064 yield z(sub0) 115.9 +/- 1.2 km and a scale height of 9.1 +/- 1.0 km. Differences between in situ and ground-based measurements show that the E region atmospheric densities were structured vertically and/or horizontally on scales of 1 km to 10 km. There were no signs of ionospheric structure in ion density or ion temperature below scales of 1 km. The observations demonstrate the accuracy with which the in situ and PFISR data may be used as probes of IT coupling.

Global-scale regionalization of hydrological model parameters using streamflow data from many small catchments

NASA Astrophysics Data System (ADS)

Beck, Hylke; de Roo, Ad; van Dijk, Albert; McVicar, Tim; Miralles, Diego; Schellekens, Jaap; Bruijnzeel, Sampurno; de Jeu, Richard

2015-04-01

Motivated by the lack of large-scale model parameter regionalization studies, a large set of 3328 small catchments (< 10000 km2) around the globe was used to set up and evaluate five model parameterization schemes at global scale. The HBV-light model was chosen because of its parsimony and flexibility to test the schemes. The catchments were calibrated against observed streamflow (Q) using an objective function incorporating both behavioral and goodness-of-fit measures, after which the catchment set was split into subsets of 1215 donor and 2113 evaluation catchments based on the calibration performance. The donor catchments were subsequently used to derive parameter sets that were transferred to similar grid cells based on a similarity measure incorporating climatic and physiographic characteristics, thereby producing parameter maps with global coverage. Overall, there was a lack of suitable donor catchments for mountainous and tropical environments. The schemes with spatially-uniform parameter sets (EXP2 and EXP3) achieved the worst Q estimation performance in the evaluation catchments, emphasizing the importance of parameter regionalization. The direct transfer of calibrated parameter sets from donor catchments to similar grid cells (scheme EXP1) performed best, although there was still a large performance gap between EXP1 and HBV-light calibrated against observed Q. The schemes with parameter sets obtained by simultaneously calibrating clusters of similar donor catchments (NC10 and NC58) performed worse than EXP1. The relatively poor Q estimation performance achieved by two (uncalibrated) macro-scale hydrological models suggests there is considerable merit in regionalizing the parameters of such models. The global HBV-light parameter maps and ancillary data are freely available via http://water.jrc.ec.europa.eu.

Multiscale/multiresolution landslides susceptibility mapping

NASA Astrophysics Data System (ADS)

Grozavu, Adrian; Cătălin Stanga, Iulian; Valeriu Patriche, Cristian; Toader Juravle, Doru

2014-05-01

Within the European strategies, landslides are considered an important threatening that requires detailed studies to identify areas where these processes could occur in the future and to design scientific and technical plans for landslide risk mitigation. In this idea, assessing and mapping the landslide susceptibility is an important preliminary step. Generally, landslide susceptibility at small scale (for large regions) can be assessed through qualitative approach (expert judgements), based on a few variables, while studies at medium and large scale requires quantitative approach (e.g. multivariate statistics), a larger set of variables and, necessarily, the landslide inventory. Obviously, the results vary more or less from a scale to another, depending on the available input data, but also on the applied methodology. Since it is almost impossible to have a complete landslide inventory on large regions (e.g. at continental level), it is very important to verify the compatibility and the validity of results obtained at different scales, identifying the differences and fixing the inherent errors. This paper aims at assessing and mapping the landslide susceptibility at regional level through a multiscale-multiresolution approach from small scale and low resolution to large scale and high resolution of data and results, comparing the compatibility of results. While the first ones could be used for studies at european and national level, the later ones allows results validation, including through fields surveys. The test area, namely the Barlad Plateau (more than 9000 sq.km) is located in Eastern Romania, covering a region where both the natural environment and the human factor create a causal context that favor these processes. The landslide predictors were initially derived from various databases available at pan-european level and progressively completed and/or enhanced together with scale and the resolution: the topography (from SRTM at 90 meters to digital elevation models based on topographical maps, 1:25,000 and 1:5,000), the lithology (from geological maps, 1:200,000), land cover and land use (from CLC 2006 to maps derived from orthorectified aerial images, 0.5 meters resolution), rainfall (from Worldclim, ECAD to our own data), the seismicity (the seismic zonation of Romania) etc. The landslide inventory was created as polygonal data based on aerial images (resolution 0.5 meters), the information being considered at county level (NUTS 3) and, eventually, at communal level (LAU2). The methodological framework is based on the logistic regression as a quantitative method and the analytic hierarchy process as a semi-qualitative methods, both being applied once identically for all scales and once recalibrated for each scale and resolution (from 1:1,000,000 and one km pixel resolution to 1:25,000 and ten meters resolution). The predictive performance of the two models was assessed using the ROC (Receiver Operating Characteristic) curve and the AUC (Area Under Curve) parameter and the results indicate a good correspondence between the susceptibility estimated for the test samples (0.855-0.890) and for the validation samples (0.830-0.865). Finally, the results were compared in pairs in order to fix the errors at small scale and low resolution and to optimize the methodology for landslide susceptibility mapping on large areas.

Open Land-Use Map: A Regional Land-Use Mapping Strategy for Incorporating OpenStreetMap with Earth Observations

NASA Astrophysics Data System (ADS)

Yang, D.; Fu, C. S.; Binford, M. W.

2017-12-01

The southeastern United States has high landscape heterogeneity, withheavily managed forestlands, highly developed agriculture lands, and multiple metropolitan areas. Human activities are transforming and altering land patterns and structures in both negative and positive manners. A land-use map for at the greater scale is a heavy computation task but is critical to most landowners, researchers, and decision makers, enabling them to make informed decisions for varying objectives. There are two major difficulties in generating the classification maps at the regional scale: the necessity of large training point sets and the expensive computation cost-in terms of both money and time-in classifier modeling. Volunteered Geographic Information (VGI) opens a new era in mapping and visualizing our world, where the platform is open for collecting valuable georeferenced information by volunteer citizens, and the data is freely available to the public. As one of the most well-known VGI initiatives, OpenStreetMap (OSM) contributes not only road network distribution, but also the potential for using this data to justify land cover and land use classifications. Google Earth Engine (GEE) is a platform designed for cloud-based mapping with a robust and fast computing power. Most large scale and national mapping approaches confuse "land cover" and "land-use", or build up the land-use database based on modeled land cover datasets. Unlike most other large-scale approaches, we distinguish and differentiate land-use from land cover. By focusing our prime objective of mapping land-use and management practices, a robust regional land-use mapping approach is developed by incorporating the OpenstreepMap dataset into Earth observation remote sensing imageries instead of the often-used land cover base maps.

Testing and comparison of three frequency-based magnitude estimating parameters for earthquake early warning based events in the Yunnan region, China in 2014

NASA Astrophysics Data System (ADS)

Zhang, Jianjing; Li, Hongjie

2018-06-01

To mitigate potential seismic disasters in the Yunnan region, China, building up suitable magnitude estimation scaling laws for an earthquake early warning system (EEWS) is in high demand. In this paper, the records from the main and after-shocks of the Yingjiang earthquake (M W 5.9), the Ludian earthquake (M W 6.2) and the Jinggu earthquake (M W 6.1), which occurred in Yunnan in 2014, were used to develop three estimators, including the maximum of the predominant period ({{τ }{{p}}}\\max ), the characteristic period (τ c) and the log-average period (τ log), for estimating earthquake magnitude. The correlations between these three frequency-based parameters and catalog magnitudes were developed, compared and evaluated against previous studies. The amplitude and period of seismic waves might be amplified in the Ludian mountain-canyon area by multiple reflections and resonance, leading to excessive values of the calculated parameters, which are consistent with Sichuan’s scaling. As a result, τ log was best correlated with magnitude and τ c had the highest slope of regression equation, while {{τ }{{p}}}\\max performed worst with large scatter and less sensitivity for the change of magnitude. No evident saturation occurred in the case of M 6.1 and M 6.2 in this study. Even though both τ c and τ log performed similarly and can well reflect the size of the Earthquake, τ log has slightly fewer prediction errors for small scale earthquakes (M ≤ 4.5), which was also observed by previous research. Our work offers an insight into the feasibility of a EEWS in Yunnan, China, and this study shows that it is necessary to build up an appropriate scaling law suitable for the warning region.

A hybrid modeling with data assimilation to evaluate human exposure level

NASA Astrophysics Data System (ADS)

Koo, Y. S.; Cheong, H. K.; Choi, D.; Kim, A. L.; Yun, H. Y.

2015-12-01

Exposure models are designed to better represent human contact with PM (Particulate Matter) and other air pollutants such as CO, SO2, O3, and NO2. The exposure concentrations of the air pollutants to human are determined by global and regional long range transport of global and regional scales from Europe and China as well as local emissions from urban and road vehicle sources. To assess the exposure level in detail, the multiple scale influence from background to local sources should be considered. A hybrid air quality modeling methodology combing a grid-based chemical transport model with a local plume dispersion model was used to provide spatially and temporally resolved air quality concentration for human exposure levels in Korea. In the hybrid modeling approach, concentrations from a grid-based chemical transport model and a local plume dispersion model are added to provide contributions from photochemical interactions, long-range (regional) transport and local-scale dispersion. The CAMx (Comprehensive Air quality Model with Extensions was used for the background concentrations from anthropogenic and natural emissions in East Asia including Korea while the road dispersion by vehicle emission was calculated by CALPUFF model. The total exposure level of the pollutants was finally assessed by summing the background and road contributions. In the hybrid modeling, the data assimilation method based on the optimal interpolation was applied to overcome the discrepancies between the model predicted concentrations and observations. The air quality data from the air quality monitoring stations in Korea. The spatial resolution of the hybrid model was 50m for the Seoul Metropolitan Ares. This example clearly demonstrates that the exposure level could be estimated to the fine scale for the exposure assessment by using the hybrid modeling approach with data assimilation.

Lumley decomposition of turbulent boundary layer at high Reynolds numbers

NASA Astrophysics Data System (ADS)

Tutkun, Murat; George, William K.

2017-02-01

The decomposition proposed by Lumley in 1966 is applied to a high Reynolds number turbulent boundary layer. The experimental database was created by a hot-wire rake of 143 probes in the Laboratoire de Mécanique de Lille wind tunnel. The Reynolds numbers based on momentum thickness (Reθ) are 9800 and 19 100. Three-dimensional decomposition is performed, namely, proper orthogonal decomposition (POD) in the inhomogeneous and bounded wall-normal direction, Fourier decomposition in the homogeneous spanwise direction, and Fourier decomposition in time. The first POD modes in both cases carry nearly 50% of turbulence kinetic energy when the energy is integrated over Fourier dimensions. The eigenspectra always peak near zero frequency and most of the large scale, energy carrying features are found at the low end of the spectra. The spanwise Fourier mode which has the largest amount of energy is the first spanwise mode and its symmetrical pair. Pre-multiplied eigenspectra have only one distinct peak and it matches the secondary peak observed in the log-layer of pre-multiplied velocity spectra. Energy carrying modes obtained from the POD scale with outer scaling parameters. Full or partial reconstruction of turbulent velocity signal based only on energetic modes or non-energetic modes revealed the behaviour of urms in distinct regions across the boundary layer. When urms is based on energetic reconstruction, there exists (a) an exponential decay from near wall to log-layer, (b) a constant layer through the log-layer, and (c) another exponential decay in the outer region. The non-energetic reconstruction reveals that urms has (a) an exponential decay from the near-wall to the end of log-layer and (b) a constant layer in the outer region. Scaling of urms using the outer parameters is best when both energetic and non-energetic profiles are combined.

A synchrotron study of defect and strain inhomogeneity in laser-assisted three-dimensionally-printed Ni-based superalloy

DOE PAGES

Li, Yao; Qian, Dan; Xue, Jiawei; ...

2015-11-02

Synchrotron X-ray microdiffraction was employed to investigate the inhomogeneous distribution of defect and residual strain in the transitional region between the dendritic and stray grains in a laser-assisted 3D printed Ni-based superalloy. The dendritic region was found to be under tensile strain transversely to the primary dendrite arm directions. The dendrite edges, where high level of strains and geometrically necessary dislocations were detected, were discerned as low angle grain boundaries. Lastly, high angle grain boundaries were observed in the stray grain region, and the orientation of the strain tensor in this region varied dramatically at the micron scale, in contrastmore » with the more or less homogeneous distribution in the dendritic region.« less

Monitoring Cloud-prone Complex Landscapes At Multiple Spatial Scales Using Medium And High Resolution Optical Data: A Case Study In Central Africa

NASA Astrophysics Data System (ADS)

Basnet, Bikash

Tracking land surface dynamics over cloud-prone areas with complex mountainous terrain and a landscape that is heterogeneous at a scale of approximately 10 m, is an important challenge in the remote sensing of tropical regions in developing nations, due to the small plot sizes. Persistent monitoring of natural resources in these regions at multiple spatial scales requires development of tools to identify emerging land cover transformation due to anthropogenic causes, such as agricultural expansion and climate change. Along with the cloud cover and obstructions by topographic distortions due to steep terrain, there are limitations to the accuracy of monitoring change using available historical satellite imagery, largely due to sparse data access and the lack of high quality ground truth for classifier training. One such complex region is the Lake Kivu region in Central Africa. This work addressed these problems to create an effective process for monitoring the Lake Kivu region located in Central Africa. The Lake Kivu region is a biodiversity hotspot with a complex and heterogeneous landscape and intensive agricultural development, where individual plot sizes are often at the scale of 10m. Procedures were developed that use optical data from satellite and aerial observations at multiple scales to tackle the monitoring challenges. First, a novel processing chain was developed to systematically monitor the spatio-temporal land cover dynamics of this region over the years 1988, 2001, and 2011 using Landsat data, complemented by ancillary data. Topographic compensation was performed on Landsat reflectances to avoid the strong illumination angle impacts and image compositing was used to compensate for frequent cloud cover and thus incomplete annual data availability in the archive. A systematic supervised classification, using the state-of-the-art machine learning classifier Random Forest, was applied to the composite Landsat imagery to obtain land cover thematic maps with overall accuracies of 90% and higher. Subsequent change analysis between these years found extensive conversions of the natural environment as a result of human related activities. The gross forest cover loss for 1988--2001 and 2001--2011 periods was 216.4 and 130.5 thousand hectares, respectively, signifying significant deforestation in the period of civil war and a relatively stable and lower deforestation rate later, possibly due to conservation and reforestation efforts in the region. The other dominant land cover changes in the region were aggressive subsistence farming and urban expansion displacing natural vegetation and arable lands. Despite limited data availability, this study fills the gap of much needed detailed and updated land cover change information for this biologically important region of Central Africa. While useful on a regional scale, Landsat data can be inadequate for more detailed studies of land cover change. Based on an increasing availability of high resolution imagery and light detection and ranging (LiDAR) data from manned and unmanned aerial platforms (<1m resolution), a study was performed leading to a novel generic framework for land cover monitoring at fine spatial scales. The approach fuses high spatial resolution aerial imagery and LiDAR data to produce land cover maps with high spatial detail using object-based image analysis techniques. The classification framework was tested for a scene with both natural and cultural features and was found to be more than 90 percent accurate, sufficient for detailed land cover change studies.

A workshop report on HIV mHealth synergy and strategy meeting to review emerging evidence-based mHealth interventions and develop a framework for scale-up of these interventions

PubMed Central

Karanja, Sarah; Mbuagbaw, Lawrence; Ritvo, Paul; Law, Judith; Kyobutungi, Catherine; Reid, Graham; Ram, Ravi; Estambale, Benson; Lester, Richard

2011-01-01

mHealth is a term used to refer to mobile technologies such as personal digital assistants and mobile phones for healthcare. mHealth initiatives to support care and treatment of patients are emerging globally and this workshop brought together researchers, policy makers, information, communication and technology programmers, academics and civil society representatives for one and a half days synergy meeting in Kenya to review regional evidence based mHealth research for HIV care and treatment, review mHealth technologies for adherence and retention interventions in anti-retroviral therapy (ART) programs and develop a framework for scale up of evidence based mHealth interventions. The workshop was held in May 2011 in Nairobi, Kenya and was funded by the Canadian Global Health Research Initiatives (GHRI) and the US Centre for Disease Control and Prevention (CDC). At the end of the workshop participants came up with a framework to guide mHealth initiatives in the region and a plan to work together in scaling up evidence based mHealth interventions. The participants acknowledged the importance of the meeting in setting the pace for strengthening and coordinating mHealth initiatives and unanimously agreed to hold a follow up meeting after three months. PMID:22187619

A workshop report on HIV mHealth synergy and strategy meeting to review emerging evidence-based mHealth interventions and develop a framework for scale-up of these interventions.

PubMed

Karanja, Sarah; Mbuagbaw, Lawrence; Ritvo, Paul; Law, Judith; Kyobutungi, Catherine; Reid, Graham; Ram, Ravi; Estambale, Benson; Lester, Richard

2011-01-01

mHealth is a term used to refer to mobile technologies such as personal digital assistants and mobile phones for healthcare. mHealth initiatives to support care and treatment of patients are emerging globally and this workshop brought together researchers, policy makers, information, communication and technology programmers, academics and civil society representatives for one and a half days synergy meeting in Kenya to review regional evidence based mHealth research for HIV care and treatment, review mHealth technologies for adherence and retention interventions in anti-retroviral therapy (ART) programs and develop a framework for scale up of evidence based mHealth interventions. The workshop was held in May 2011 in Nairobi, Kenya and was funded by the Canadian Global Health Research Initiatives (GHRI) and the US Centre for Disease Control and Prevention (CDC). At the end of the workshop participants came up with a framework to guide mHealth initiatives in the region and a plan to work together in scaling up evidence based mHealth interventions. The participants acknowledged the importance of the meeting in setting the pace for strengthening and coordinating mHealth initiatives and unanimously agreed to hold a follow up meeting after three months.

The economic-wide consequences of large-scale floods. How resilient is the European economy?

NASA Astrophysics Data System (ADS)

Koks, Elco; Thissen, Mark; De Moel, Hans; Aerts, Jeroen

2015-04-01

For a successful adaptation strategy, it is necessary to have an in-depth understanding of the economic consequences of a flood. To assess the economic consequences of large-scale river floods in Europe, we introduce an integrated direct and indirect risk model for the European economy as a whole. The proposed methodology consists of multiple steps. First, a direct loss assessment is conducted for the 50 largest river basin districts in Europe, based on simulated floods for several return periods. Second, the direct losses in capital and labour are translated into the loss in production per sector. Third, the recovery of this production shock is modelled using a hybrid interregional input-output model, combining non-linear programming and input-output modelling. This combination makes it possible to find (1) the possible production losses in the affected regions and other European regions, (2) the required production in Europe to satisfy additional reconstruction demands from the affected regions and (3) the required production in other regions that is necessary to take over lost production in the affected region. Consequently, when knowing how much production is lost (or gained) in each region, the economic consequences can be assessed. Finally, the model outcome is loss estimation expressed in terms of expected annual damage. To assess these consequences, interregional supply and use tables are used, consisting of 256 different European NUTS2 regions. This data makes it possible to model the indirect losses for both the affected regions and the rest of Europe in detail. By combining the outcomes of all floods in all the river basin districts, it is possible to determine the flood risk of each region in Europe, even when a region is not directly hit by a flood. Consequently, the overall consequences for the European Union are found to be positive for small-scale floods and negative for large-scale floods.

Regional-scale calculation of the LS factor using parallel processing

NASA Astrophysics Data System (ADS)

Liu, Kai; Tang, Guoan; Jiang, Ling; Zhu, A.-Xing; Yang, Jianyi; Song, Xiaodong

2015-05-01

With the increase of data resolution and the increasing application of USLE over large areas, the existing serial implementation of algorithms for computing the LS factor is becoming a bottleneck. In this paper, a parallel processing model based on message passing interface (MPI) is presented for the calculation of the LS factor, so that massive datasets at a regional scale can be processed efficiently. The parallel model contains algorithms for calculating flow direction, flow accumulation, drainage network, slope, slope length and the LS factor. According to the existence of data dependence, the algorithms are divided into local algorithms and global algorithms. Parallel strategy are designed according to the algorithm characters including the decomposition method for maintaining the integrity of the results, optimized workflow for reducing the time taken for exporting the unnecessary intermediate data and a buffer-communication-computation strategy for improving the communication efficiency. Experiments on a multi-node system show that the proposed parallel model allows efficient calculation of the LS factor at a regional scale with a massive dataset.

Automated Detection of Microaneurysms Using Scale-Adapted Blob Analysis and Semi-Supervised Learning

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

Adal, Kedir M.; Sidebe, Desire; Ali, Sharib

2014-01-07

Despite several attempts, automated detection of microaneurysm (MA) from digital fundus images still remains to be an open issue. This is due to the subtle nature of MAs against the surrounding tissues. In this paper, the microaneurysm detection problem is modeled as finding interest regions or blobs from an image and an automatic local-scale selection technique is presented. Several scale-adapted region descriptors are then introduced to characterize these blob regions. A semi-supervised based learning approach, which requires few manually annotated learning examples, is also proposed to train a classifier to detect true MAs. The developed system is built using onlymore » few manually labeled and a large number of unlabeled retinal color fundus images. The performance of the overall system is evaluated on Retinopathy Online Challenge (ROC) competition database. A competition performance measure (CPM) of 0.364 shows the competitiveness of the proposed system against state-of-the art techniques as well as the applicability of the proposed features to analyze fundus images.« less

Variations of Scale Height at F-Region Peak Based on Ionosonde Measurements during Solar Maximum over the Crest of Equatorial Ionization Anomaly Region

PubMed Central

Chuo, Yu-Jung

2014-01-01

Scale height is an important parameter in characterizing the shape of the ionosphere and its physical processes. In this study, we attempt to examine and discuss the variation of scale height, H m, around the F-layer peak height during high solar activity at the northern crest of the equatorial ionization anomaly (EIA) region. H m exhibits day-to-day variation and seasonal variation, with a greater average daily variation during daytime in summer. Furthermore, the diurnal variation of H m exhibits an abnormal peak at presunrise during all the seasons, particularly in winter. This increase is also observed in the F2-layer peak height for the same duration with an upward movement associated with thermospheric wind toward the equator; this upward movement increases the N2/O ratio and H m, but it causes a decrease in the F2-layer maximum critical frequency during the presunrise period. PMID:25162048

Improving National Capability in Biogeochemical Flux Modelling: the UK Environmental Virtual Observatory (EVOp)

NASA Astrophysics Data System (ADS)

Johnes, P.; Greene, S.; Freer, J. E.; Bloomfield, J.; Macleod, K.; Reaney, S. M.; Odoni, N. A.

2012-12-01

The best outcomes from watershed management arise where policy and mitigation efforts are underpinned by strong science evidence, but there are major resourcing problems associated with the scale of monitoring needed to effectively characterise the sources rates and impacts of nutrient enrichment nationally. The challenge is to increase national capability in predictive modelling of nutrient flux to waters, securing an effective mechanism for transferring knowledge and management tools from data-rich to data-poor regions. The inadequacy of existing tools and approaches to address these challenges provided the motivation for the Environmental Virtual Observatory programme (EVOp), an innovation from the UK Natural Environment Research Council (NERC). EVOp is exploring the use of a cloud-based infrastructure in catchment science, developing an exemplar to explore N and P fluxes to inland and coastal waters in the UK from grid to catchment and national scale. EVOp is bringing together for the first time national data sets, models and uncertainty analysis into cloud computing environments to explore and benchmark current predictive capability for national scale biogeochemical modelling. The objective is to develop national biogeochemical modelling capability, capitalising on extensive national investment in the development of science understanding and modelling tools to support integrated catchment management, and supporting knowledge transfer from data rich to data poor regions, The AERC export coefficient model (Johnes et al., 2007) has been adapted to function within the EVOp cloud environment, and on a geoclimatic basis, using a range of high resolution, geo-referenced digital datasets as an initial demonstration of the enhanced national capacity for N and P flux modelling using cloud computing infrastructure. Geoclimatic regions are landscape units displaying homogenous or quasi-homogenous functional behaviour in terms of process controls on N and P cycling, underpin this approach (Johnes & Butterfield, 2002). Ten regions have been defined across the UK using GIS manipulation of spatial data describing hydrogeology, runoff, topographical slope and soil parent material. The export coefficient model operates within this regional modelling framework, providing mapped, tabulated and statistical outputs at scales from 1km2 grid scale to river catchment, WFD river basin district, major coastal drainage units to the North Sea, North Atlantic and English Channel, to the international reporting units defined under OSPAR, the International Convention for the protection of the marine environment of the North-East Atlantic. Here the geoclimatic modelling framework is presented together with modelled fluxes for N and P for each scale of reporting unit, together with scenario analysis applied at regional scale and mapped at national scale. The ways in which the results can be used to further explore the primary drivers for spatial variation and identify waterbodies at risk, especially in unmonitored and data-poor catchments are discussed, and the technical and computational support of a cloud-based infrastructure is evaluated as a mechanism to explore potential water quality impacts of future mitigation strategies applied at catchment to national scale.

Geologic map of the Galaxias quadrangle (MTM 35217) of Mars

USGS Publications Warehouse

De Hon, Rene A.; Mouginis-Mark, Peter J.; Brick, Eugene E.

1999-01-01

The Galaxias region (MTM 35217) is one of a series of 1:500,000-scale science study areas on Mars sponsored by NASA's Planetary Geology and Geophysics Program. Situated near the northern limit of lava flows associated with Elysium Mons, this region includes a mixture of volcanic and nonvolcanic terrains. The region is also of interest for the fluvial systems that originate along the distal margins of the Elysium lava flows. Resolution of Viking Orbiter images used to prepare the base map ranges from 40 to 160 m/pixel. High-resolution frames (40 to 80 m/pixel) are found in the southeastern part of the map area and along the north edge of the quadrangle, but over half the quadrangle is included in medium-resolution frames (150 m/pixel). Two 8 m/pixel, very high resolution scenes are available (see fig. 1). Interpretation is complicated by variable resolution and sun angles that vary from east to west illumination on different images. Mapping methods and principles are adapted from those developed for lunar photogeologic mapping by Shoemaker and Hackman (1962), refined by Wilhelms (1972), and successfully applied by many workers to a variety of planetary surfaces. Mapping units are distinguished by topography and texture and are ranked by relative age on the basis of superposition and transection relations. Material units are assigned to time-stratigraphic systems defined by Scott and Carr (1978) and Tanaka (1986). This area is included within earlier maps that used Mariner 9 images at 1:5,000,000 scale (Elston, 1979) and globally at 1:25,000,000 scale (Scott and Carr, 1978). Regional maps based on the much higher resolutions of Viking Orbiter allowed more detailed discrimination of materials by Greeley and Guest (1987) at 1:15,000,000 scale and Tanaka and others (1992) at 1:5,000,000 scale. Some map units on this 1:500,000-scale map correspond to, or are partially equivalent to, units on the larger scale maps of Greeley and Guest (1987) and Tanaka and others (1992). Established terminology is used where feasible, but the scale of this map requires that some new units be introduced and that some previous terminology be redefined. Photogeologic methods are limited; therefore, more than one geologic explanation is given for some material units that do not readily lend themselves to an unequivocal interpretation.

A priori testing of subgrid-scale models for large-eddy simulation of the atmospheric boundary layer

NASA Astrophysics Data System (ADS)

Juneja, Anurag; Brasseur, James G.

1996-11-01

Subgrid-scale models are generally developed assuming homogeneous isotropic turbulence with the filter cutoff lying in the inertial range. In the surface layer and capping inversion regions of the atmospheric boundary layer, the turbulence is strongly anisotropic and, in general, influenced by both buoyancy and shear. Furthermore, the integral scale motions are under-resolved in these regions. Herein we perform direct numerical simulations of shear and buoyancy-generated homogeneous anisotropic turbulence to compute and analyze the actual subgrid-resolved-scale (SGS-RS) dynamics as the filter cutoff moves into the energy-containing scales. These are compared with the SGS-RS dynamics predicted by Smagorinsky-based models with a focus on motivating improved closures. We find that, in general, the underlying assumption of such models, that the anisotropic part of the subgrid stress tensor be aligned with the resolved strain rate tensor, is a poor approximation. Similarly, we find poor alignment between the actual and predicted stress divergence, and find low correlations between the actual and modeled subgrid-scale contribution to the pressure and pressure gradient. Details will be given in the talk.

Exploring the role of movement in determining the global distribution of marine biomass using a coupled hydrodynamic - Size-based ecosystem model

NASA Astrophysics Data System (ADS)

Watson, James R.; Stock, Charles A.; Sarmiento, Jorge L.

2015-11-01

Modeling the dynamics of marine populations at a global scale - from phytoplankton to fish - is necessary if we are to quantify how climate change and other broad-scale anthropogenic actions affect the supply of marine-based food. Here, we estimate the abundance and distribution of fish biomass using a simple size-based food web model coupled to simulations of global ocean physics and biogeochemistry. We focus on the spatial distribution of biomass, identifying highly productive regions - shelf seas, western boundary currents and major upwelling zones. In the absence of fishing, we estimate the total ocean fish biomass to be ∼ 2.84 ×109 tonnes, similar to previous estimates. However, this value is sensitive to the choice of parameters, and further, allowing fish to move had a profound impact on the spatial distribution of fish biomass and the structure of marine communities. In particular, when movement is implemented the viable range of large predators is greatly increased, and stunted biomass spectra characterizing large ocean regions in simulations without movement, are replaced with expanded spectra that include large predators. These results highlight the importance of considering movement in global-scale ecological models.

Single-Image Super-Resolution Based on Rational Fractal Interpolation.

PubMed

Zhang, Yunfeng; Fan, Qinglan; Bao, Fangxun; Liu, Yifang; Zhang, Caiming

2018-08-01

This paper presents a novel single-image super-resolution (SR) procedure, which upscales a given low-resolution (LR) input image to a high-resolution image while preserving the textural and structural information. First, we construct a new type of bivariate rational fractal interpolation model and investigate its analytical properties. This model has different forms of expression with various values of the scaling factors and shape parameters; thus, it can be employed to better describe image features than current interpolation schemes. Furthermore, this model combines the advantages of rational interpolation and fractal interpolation, and its effectiveness is validated through theoretical analysis. Second, we develop a single-image SR algorithm based on the proposed model. The LR input image is divided into texture and non-texture regions, and then, the image is interpolated according to the characteristics of the local structure. Specifically, in the texture region, the scaling factor calculation is the critical step. We present a method to accurately calculate scaling factors based on local fractal analysis. Extensive experiments and comparisons with the other state-of-the-art methods show that our algorithm achieves competitive performance, with finer details and sharper edges.

Analysis of extreme hydrological phenomena in southern Italy (Calabria region)

NASA Astrophysics Data System (ADS)

Caloiero, Tommaso; Aceto, Luigi; Aurora Pasqua, A.; Petrucci, Olga

2017-04-01

Calabria (southern Italy) is a region exposed to the effects of contrasting climatic and hydrological phenomena. In fact, due to its oblong shape, to its position in the middle of the Mediterranean Basin, and for its mountainous nature, Calabria shows a high spatial variability of the climatic features and of related phenomena such as floods and drought. The present paper is based on the historical database ASICal (Historically flooded areas in Calabria), a catalogue of effects of floods and rain-related landslides that occurred in the region since the XIX Century. The catalogue has been built using the typical historical data sources as chronicles, diaries, historical books, local and regional agencies, press archives, scientific papers, and documents of civil protection offices. From these sources, we selected information on damage caused by rain related phenomena at a municipal scale and chronologically sorted by year, month and day. The analysis of the entire catalogue allows highlighting the regional Damaging Hydrogeological Events (DHE), defined as periods of intense rain causing damage on regional sectors conventionally selected as larger than 30% of the entire regional territory. For each event, as a measure of the magnitude of rainfall, the return period of the daily rainfall recorded during the event has been evaluated. In addition, we recently carried out a similar historical research to identify the main drought events affecting the region. In this case, due to the spatial and temporal characteristics of drought, data are collected both at municipal and regional scale, and the temporal scale is generally monthly or annual. For each event, we used as climatic descriptors a drought index for monitoring drought phenomena. Among drought indices, we used the Standardized Precipitation Index (SPI) which can be considered the most robust and effective, since it can be calculated for different time-scales and can be used to analyse different drought categories. Moreover, the SPI is easier to calculate than complex indices, as it is based on precipitation alone, and allows comparing drought conditions among different periods and regions. Both the series have been analysed jointly, in order to obtain the general trend of extreme rain and drought, characterised by mean of descriptive climatic features and damage caused. The results supply a glance in the past climatic history of the region that can be used to project to future and be prepared for ongoing changes related to climate changes. In fact, the identification of the most floods and drought prone areas can be useful for both civil protection mitigation strategies and water resources management (water used for home, industrial, and agricultural purposes).

Convergence and divergence in a long-term old-field succession: the importance of spatial scale and species abundance.

PubMed

Li, Shao-Peng; Cadotte, Marc W; Meiners, Scott J; Pu, Zhichao; Fukami, Tadashi; Jiang, Lin

2016-09-01

Whether plant communities in a given region converge towards a particular stable state during succession has long been debated, but rarely tested at a sufficiently long time scale. By analysing a 50-year continuous study of post-agricultural secondary succession in New Jersey, USA, we show that the extent of community convergence varies with the spatial scale and species abundance classes. At the larger field scale, abundance-based dissimilarities among communities decreased over time, indicating convergence of dominant species, whereas incidence-based dissimilarities showed little temporal tend, indicating no sign of convergence. In contrast, plots within each field diverged in both species composition and abundance. Abundance-based successional rates decreased over time, whereas rare species and herbaceous plants showed little change in temporal turnover rates. Initial abandonment conditions only influenced community structure early in succession. Overall, our findings provide strong evidence for scale and abundance dependence of stochastic and deterministic processes over old-field succession. © 2016 John Wiley & Sons Ltd/CNRS.

Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands

NASA Astrophysics Data System (ADS)

Ju, Weimin; Gao, Ping; Wang, Jun; Li, Xianfeng; Chen, Shu

2008-10-01

Soil water content (SWC) is an important factor affecting photosynthesis, growth, and final yields of crops. The information on SWC is of importance for mitigating the reduction of crop yields caused by drought through proper agricultural water management. A variety of methodologies have been developed to estimate SWC at local and regional scales, including field sampling, remote sensing monitoring and model simulations. The reliability of regional SWC simulation depends largely on the accuracy of spatial input datasets, including vegetation parameters, soil and meteorological data. Remote sensing has been proved to be an effective technique for controlling uncertainties in vegetation parameters. In this study, the vegetation parameters (leaf area index and land cover type) derived from the Moderate Resolution Imaging Spectrometer (MODIS) were assimilated into a process-based ecosystem model BEPS for simulating the variations of SWC in croplands of Jiangsu province, China. Validation shows that the BEPS model is able to capture 81% and 83% of across-site variations of SWC at 10 and 20 cm depths during the period from September to December, 2006 when a serous autumn drought occurred. The simulated SWC responded the events of rainfall well at regional scale, demonstrating the usefulness of our methodology for SWC and practical agricultural water management at large scales.

Similar Processes but Different Environmental Filters for Soil Bacterial and Fungal Community Composition Turnover on a Broad Spatial Scale

PubMed Central

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P. A.; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

PubMed

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

DO NOT FORGET THE FOREST FOR THE TREES: THE STELLAR-MASS HALO-MASS RELATION IN DIFFERENT ENVIRONMENTS

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

Tonnesen, Stephanie; Cen, Renyue, E-mail: stonnes@gmail.com, E-mail: cen@astro.princeton.edu

2015-10-20

The connection between dark matter halos and galactic baryons is often not well constrained nor well resolved in cosmological hydrodynamical simulations. Thus, halo occupation distribution models that assign galaxies to halos based on halo mass are frequently used to interpret clustering observations, even though it is well known that the assembly history of dark matter halos is related to their clustering. In this paper we use high-resolution hydrodynamical cosmological simulations to compare the halo and stellar mass growth of galaxies in a large-scale overdensity to those in a large-scale underdensity (on scales of about 20 Mpc). The simulation reproduces assemblymore » bias, in which halos have earlier formation times in overdense environments than in underdense regions. We find that the ratio of stellar mass to halo mass is larger in overdense regions in central galaxies residing in halos with masses between 10{sup 11} and 10{sup 12.9} M{sub ⊙}. When we force the local density (within 2 Mpc) at z = 0 to be the same for galaxies in the large-scale over- and underdensities, we find the same results. We posit that this difference can be explained by a combination of earlier formation times, more interactions at early times with neighbors, and more filaments feeding galaxies in overdense regions. This result puts the standard practice of assigning stellar mass to halos based only on their mass, rather than considering their larger environment, into question.« less

A Dynamic Evaluation Of A Model And An Estimate Of The Air Quality And Regional Climate Impacts Of Enhanced Solar Power Generation

NASA Astrophysics Data System (ADS)

Millstein, D.; Brown, N. J.; Zhai, P.; Menon, S.

2012-12-01

We use the WRF/Chem model (Weather Research and Forecasting model with chemistry) and pollutant emissions based on the EPA National Emission Inventories from 2005 and 2008 to model regional climate and air quality over the continental United States. Additionally, 2030 emission scenarios are developed to investigate the effects of future enhancements to solar power generation. Modeling covered 6 summer and 6 winter weeks each year. We model feedback between aerosols and meteorology and thus capture direct and indirect aerosol effects. The grid resolution is 25 km and includes no nesting. Between 2005 and 2008 significant emission reductions were reported in the National Emission Inventory. The 2008 weekday emissions over the continental U.S. of SO2 and NO were reduced from 2005 values by 28% and 16%, respectively. Emission reductions of this magnitude are similar in scale to the potential emission reductions from various energy policy initiatives. By evaluating modeled and observed air quality changes from 2005 to 2008, we analyze how well the model represents the effects of historical emission changes. We also gain insight into how well the model might predict the effects of future emission changes. In addition to direct comparisons of model outputs to ground and satellite observations, we compare observed differences between 2005 and 2008 to corresponding modeled differences. Modeling was extended to future scenarios (2030) to simulate air quality and regional climate effects of large-scale adoption of solar power. The 2030-year was selected to allow time for development of solar generation infrastructure. The 2030 emission scenario was scaled, with separate factors for different economic sectors, from the 2008 National Emissions Inventory. The changes to emissions caused by the introduction of large-scale solar power (here assumed to be 10% of total energy generation) are based on results from a parallel project that used an electricity grid model applied over multiple regions across the country. The regional climate and air quality effects of future large-scale solar power adoption are analyzed in the context of uncertainty quantified by the dynamic evaluation of the historical (2005 and 2008) WRF/Chem simulations.

Revisiting Cholera-Climate Teleconnections in the Native Homeland: ENSO and other Extremes through the Regional Hydroclimatic Drivers

NASA Astrophysics Data System (ADS)

Akanda, A. S.; Jutla, A.; Huq, A.; Colwell, R. R.

2014-12-01

Cholera is a global disease, with significantly large outbreaks occurring since the 1990s, notably in Sub-Saharan Africa and South Asia and recently in Haiti, in the Caribbean. Critical knowledge gaps remain in the understanding of the annual recurrence in endemic areas and the nature of epidemic outbreaks, especially those that follow extreme hydroclimatic events. Teleconnections with large-scale climate phenomena affecting regional scale hydroclimatic drivers of cholera dynamics remain largely unexplained. For centuries, the Bengal delta region has been strongly influenced by the asymmetric availability of water in the rivers Ganges and the Brahmaputra. As these two major rivers are known to have strong contrasting affects on local cholera dynamics in the region, we argue that the role of El Nino-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), or other phenomena needs to be interpreted in the context of the seasonal role of individual rivers and subsequent impact on local environmental processes, not as a teleconnection having a remote and unified effect. We present a modified hypothesis that the influences of large-scale climate phenomena such as ENSO and IOD on Bengal cholera can be explicitly identified and incorporated through regional scale hydroclimatic drivers. Here, we provide an analytical review of the literature addressing cholera and climate linkages and present hypotheses, based on recent evidence, and quantification on the role of regional scale hydroclimatic drivers of cholera. We argue that the seasonal changes in precipitation and temperature, and resulting river discharge in the GBM basin region during ENSO and IOD events have a dominant combined effect on the endemic persistence and the epidemic vulnerability to cholera outbreaks in spring and fall seasons, respectively, that is stronger than the effect of localized hydrological and socio-economic sensitivities in Bangladesh. In addition, systematic identification of underlying seasonal hydroclimatic drivers will allow us to harness the inherent system memory of these processes to develop early warning systems and strengthen prevention measures.

Connotations of pixel-based scale effect in remote sensing and the modified fractal-based analysis method

NASA Astrophysics Data System (ADS)

Feng, Guixiang; Ming, Dongping; Wang, Min; Yang, Jianyu

2017-06-01

Scale problems are a major source of concern in the field of remote sensing. Since the remote sensing is a complex technology system, there is a lack of enough cognition on the connotation of scale and scale effect in remote sensing. Thus, this paper first introduces the connotations of pixel-based scale and summarizes the general understanding of pixel-based scale effect. Pixel-based scale effect analysis is essentially important for choosing the appropriate remote sensing data and the proper processing parameters. Fractal dimension is a useful measurement to analysis pixel-based scale. However in traditional fractal dimension calculation, the impact of spatial resolution is not considered, which leads that the scale effect change with spatial resolution can't be clearly reflected. Therefore, this paper proposes to use spatial resolution as the modified scale parameter of two fractal methods to further analyze the pixel-based scale effect. To verify the results of two modified methods (MFBM (Modified Windowed Fractal Brownian Motion Based on the Surface Area) and MDBM (Modified Windowed Double Blanket Method)); the existing scale effect analysis method (information entropy method) is used to evaluate. And six sub-regions of building areas and farmland areas were cut out from QuickBird images to be used as the experimental data. The results of the experiment show that both the fractal dimension and information entropy present the same trend with the decrease of spatial resolution, and some inflection points appear at the same feature scales. Further analysis shows that these feature scales (corresponding to the inflection points) are related to the actual sizes of the geo-object, which results in fewer mixed pixels in the image, and these inflection points are significantly indicative of the observed features. Therefore, the experiment results indicate that the modified fractal methods are effective to reflect the pixel-based scale effect existing in remote sensing data and it is helpful to analyze the observation scale from different aspects. This research will ultimately benefit for remote sensing data selection and application.

Attribution of spring snow water equivalent (SWE) changes over the northern hemisphere to anthropogenic effects

NASA Astrophysics Data System (ADS)

Jeong, Dae Il; Sushama, Laxmi; Naveed Khaliq, M.

2017-06-01

Snow is an important component of the cryosphere and it has a direct and important influence on water storage and supply in snowmelt-dominated regions. This study evaluates the temporal evolution of snow water equivalent (SWE) for the February-April spring period using the GlobSnow observation dataset for the 1980-2012 period. The analysis is performed for different regions of hemispherical to sub-continental scales for the Northern Hemisphere. The detection-attribution analysis is then performed to demonstrate anthropogenic and natural effects on spring SWE changes for different regions, by comparing observations with six CMIP5 model simulations for three different external forcings: all major anthropogenic and natural (ALL) forcings, greenhouse gas (GHG) forcing only, and natural forcing only. The observed spring SWE generally displays a decreasing trend, due to increasing spring temperatures. However, it exhibits a remarkable increasing trend for the southern parts of East Eurasia. The six CMIP5 models with ALL forcings reproduce well the observed spring SWE decreases at the hemispherical scale and continental scales, whereas important differences are noted for smaller regions such as southern and northern parts of East Eurasia and northern part of North America. The effects of ALL and GHG forcings are clearly detected for the spring SWE decline at the hemispherical scale, based on multi-model ensemble signals. The effects of ALL and GHG forcings, however, are less clear for the smaller regions or with single-model signals, indicating the large uncertainty in regional SWE changes, possibly due to stronger influence of natural climate variability.

Regional analysis and derivation of copula-based drought Severity-Area-Frequency curve in Lake Urmia basin, Iran.

PubMed

Amirataee, Babak; Montaseri, Majid; Rezaie, Hossein

2018-01-15

Droughts are extreme events characterized by temporal duration and spatial large-scale effects. In general, regional droughts are affected by general circulation of the atmosphere (at large-scale) and regional natural factors, including the topography, natural lakes, the position relative to the center and the path of the ocean currents (at small-scale), and they don't cover the exact same effects in a wide area. Therefore, drought Severity-Area-Frequency (S-A-F) curve investigation is an essential task to develop decision making rule for regional drought management. This study developed the copula-based joint probability distribution of drought severity and percent of area under drought across the Lake Urmia basin, Iran. To do this end, one-month Standardized Precipitation Index (SPI) values during the 1971-2013 were applied across 24 rainfall stations in the study area. Then, seven copula functions of various families, including Clayton, Gumbel, Frank, Joe, Galambos, Plackett and Normal copulas, were used to model the joint probability distribution of drought severity and drought area. Using AIC, BIC and RMSE criteria, the Frank copula was selected as the most appropriate copula in order to develop the joint probability distribution of severity-percent of area under drought across the study area. Based on the Frank copula, the drought S-A-F curve for the study area was derived. The results indicated that severe/extreme drought and non-drought (wet) behaviors have affected the majority of study areas (Lake Urmia basin). However, the area covered by the specific semi-drought effects is limited and has been subject to significant variations. Copyright © 2017 Elsevier Ltd. All rights reserved.

A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale

NASA Astrophysics Data System (ADS)

Zhang, Shaojie; Zhao, Luqiang; Delgado-Tellez, Ricardo; Bao, Hongjun

2018-03-01

Conventional outputs of physics-based landslide forecasting models are presented as deterministic warnings by calculating the safety factor (Fs) of potentially dangerous slopes. However, these models are highly dependent on variables such as cohesion force and internal friction angle which are affected by a high degree of uncertainty especially at a regional scale, resulting in unacceptable uncertainties of Fs. Under such circumstances, the outputs of physical models are more suitable if presented in the form of landslide probability values. In order to develop such models, a method to link the uncertainty of soil parameter values with landslide probability is devised. This paper proposes the use of Monte Carlo methods to quantitatively express uncertainty by assigning random values to physical variables inside a defined interval. The inequality Fs < 1 is tested for each pixel in n simulations which are integrated in a unique parameter. This parameter links the landslide probability to the uncertainties of soil mechanical parameters and is used to create a physics-based probabilistic forecasting model for rainfall-induced shallow landslides. The prediction ability of this model was tested in a case study, in which simulated forecasting of landslide disasters associated with heavy rainfalls on 9 July 2013 in the Wenchuan earthquake region of Sichuan province, China, was performed. The proposed model successfully forecasted landslides in 159 of the 176 disaster points registered by the geo-environmental monitoring station of Sichuan province. Such testing results indicate that the new model can be operated in a highly efficient way and show more reliable results, attributable to its high prediction accuracy. Accordingly, the new model can be potentially packaged into a forecasting system for shallow landslides providing technological support for the mitigation of these disasters at regional scale.

Development of WRF-CO2 4DVAR Data Assimilation System

NASA Astrophysics Data System (ADS)

Zheng, T.; French, N. H. F.

2016-12-01

Four dimensional variational (4DVar) assimilation systems have been widely used for CO2 inverse modeling at global scale. At regional scale, however, 4DVar assimilation systems have been lacking. At present, most regional CO2 inverse models use Lagrangian particle backward trajectory tools to compute influence function in an analytical/synthesis framework. To provide a 4DVar based alternative, we developed WRF-CO2 4DVAR based on Weather Research and Forecasting (WRF), its chemistry extension (WRF-Chem), and its data assimilation system (WRFDA/WRFPLUS). Different from WRFDA, WRF-CO2 4DVAR does not optimize meteorology initial condition, instead it solves for the optimized CO2 surface fluxes (sources/sink) constrained by atmospheric CO2 observations. Based on WRFPLUS, we developed tangent linear and adjoint code for CO2 emission, advection, vertical mixing in boundary layer, and convective transport. Furthermore, we implemented an incremental algorithm to solve for optimized CO2 emission scaling factors by iteratively minimizing the cost function in a Bayes framework. The model sensitivity (of atmospheric CO2 with respect to emission scaling factor) calculated by tangent linear and adjoint model agrees well with that calculated by finite difference, indicating the validity of the newly developed code. The effectiveness of WRF-CO2 4DVar for inverse modeling is tested using forward-model generated pseudo-observation data in two experiments: first-guess CO2 fluxes has a 50% overestimation in the first case and 50% underestimation in the second. In both cases, WRF-CO2 4DVar reduces cost function to less than 10-4 of its initial values in less than 20 iterations and successfully recovers the true values of emission scaling factors. We expect future applications of WRF-CO2 4DVar with satellite observations will provide insights for CO2 regional inverse modeling, including the impacts of model transport error in vertical mixing.

Upscaling and Downscaling of Land Surface Fluxes with Surface Temperature

NASA Astrophysics Data System (ADS)

Kustas, W. P.; Anderson, M. C.; Hain, C.; Albertson, J. D.; Gao, F.; Yang, Y.

2015-12-01

Land surface temperature (LST) is a key surface boundary condition that is significantly correlated to surface flux partitioning between latent and sensible heat. The spatial and temporal variation in LST is driven by radiation, wind, vegetation cover and roughness as well as soil moisture status in the surface and root zone. Data from airborne and satellite-based platforms provide LST from ~10 km to sub meter resolutions. A land surface scheme called the Two-Source Energy Balance (TSEB) model has been incorporated into a multi-scale regional modeling system ALEXI (Atmosphere Land Exchange Inverse) and a disaggregation scheme (DisALEXI) using higher resolution LST. Results with this modeling system indicates that it can be applied over heterogeneous land surfaces and estimate reliable surface fluxes with minimal in situ information. Consequently, this modeling system allows for scaling energy fluxes from subfield to regional scales in regions with little ground data. In addition, the TSEB scheme has been incorporated into a large Eddy Simulation (LES) model for investigating dynamic interactions between variations in the land surface state reflected in the spatial pattern in LST and the lower atmospheric air properties affecting energy exchange. An overview of research results on scaling of fluxes and interactions with the lower atmosphere from the subfield level to regional scales using the TSEB, ALEX/DisALEX and the LES-TSEB approaches will be presented. Some unresolved issues in the use of LST at different spatial resolutions for estimating surface energy balance and upscaling fluxes, particularly evapotranspiration, will be discussed.

Karst medium characterization and simulation of groundwater flow in Lijiang Riversed, China

NASA Astrophysics Data System (ADS)

Hu, B. X.

2015-12-01

It is important to study water and carbon cycle processes for water resource management, pollution prevention and global warming influence on southwest karst region of China. Lijiang river basin is selected as our study region. Interdisciplinary field and laboratory experiments with various technologies are conducted to characterize the karst aquifers in detail. Key processes in the karst water cycle and carbon cycle are determined. Based on the MODFLOW-CFP model, new watershed flow and carbon cycle models are developed coupled subsurface and surface water flow models, flow and chemical/biological models. Our study is focused on the karst springshed in Mao village. The mechanisms coupling carbon cycle and water cycle are explored. Parallel computing technology is used to construct the numerical model for the carbon cycle and water cycle in the small scale watershed, which are calibrated and verified by field observations. The developed coupling model for the small scale watershed is extended to a large scale watershed considering the scale effect of model parameters and proper model structure simplification. The large scale watershed model is used to study water cycle and carbon cycle in Lijiang rivershed, and to calculate the carbon flux and carbon sinks in the Lijiang river basin. The study results provide scientific methods for water resources management and environmental protection in southwest karst region corresponding to global climate change. This study could provide basic theory and simulation method for geological carbon sequestration in China karst region.

Simulation of groundwater flow and evaluation of carbon sink in Lijiang Rivershed, China

NASA Astrophysics Data System (ADS)

Hu, Bill X.; Cao, Jianhua; Tong, Juxiu; Gao, Bing

2016-04-01

It is important to study water and carbon cycle processes for water resource management, pollution prevention and global warming influence on southwest karst region of China. Lijiang river basin is selected as our study region. Interdisciplinary field and laboratory experiments with various technologies are conducted to characterize the karst aquifers in detail. Key processes in the karst water cycle and carbon cycle are determined. Based on the MODFLOW-CFP model, new watershed flow and carbon cycle models are developed coupled subsurface and surface water flow models, flow and chemical/biological models. Our study is focused on the karst springshed in Mao village. The mechanisms coupling carbon cycle and water cycle are explored. Parallel computing technology is used to construct the numerical model for the carbon cycle and water cycle in the small scale watershed, which are calibrated and verified by field observations. The developed coupling model for the small scale watershed is extended to a large scale watershed considering the scale effect of model parameters and proper model structure simplification. The large scale watershed model is used to study water cycle and carbon cycle in Lijiang rivershed, and to calculate the carbon flux and carbon sinks in the Lijiang river basin. The study results provide scientific methods for water resources management and environmental protection in southwest karst region corresponding to global climate change. This study could provide basic theory and simulation method for geological carbon sequestration in China karst region.

Seeds Of Life In Space (SOLIS): The Organic Composition Diversity at 300-1000 au Scale in Solar-type Star-forming Regions

NASA Astrophysics Data System (ADS)

Ceccarelli, C.; Caselli, P.; Fontani, F.; Neri, R.; López-Sepulcre, A.; Codella, C.; Feng, S.; Jiménez-Serra, I.; Lefloch, B.; Pineda, J. E.; Vastel, C.; Alves, F.; Bachiller, R.; Balucani, N.; Bianchi, E.; Bizzocchi, L.; Bottinelli, S.; Caux, E.; Chacón-Tanarro, A.; Choudhury, R.; Coutens, A.; Dulieu, F.; Favre, C.; Hily-Blant, P.; Holdship, J.; Kahane, C.; Jaber Al-Edhari, A.; Laas, J.; Ospina, J.; Oya, Y.; Podio, L.; Pon, A.; Punanova, A.; Quenard, D.; Rimola, A.; Sakai, N.; Sims, I. R.; Spezzano, S.; Taquet, V.; Testi, L.; Theulé, P.; Ugliengo, P.; Vasyunin, A. I.; Viti, S.; Wiesenfeld, L.; Yamamoto, S.

2017-12-01

Complex organic molecules have been observed for decades in the interstellar medium. Some of them might be considered as small bricks of the macromolecules at the base of terrestrial life. It is hence particularly important to understand organic chemistry in Solar-like star-forming regions. In this article, we present a new observational project: Seeds Of Life In Space (SOLIS). This is a Large Project using the IRAM-NOEMA interferometer, and its scope is to image the emission of several crucial organic molecules in a sample of Solar-like star-forming regions in different evolutionary stages and environments. Here we report the first SOLIS results, obtained from analyzing the spectra of different regions of the Class 0 source NGC 1333-IRAS4A, the protocluster OMC-2 FIR4, and the shock site L1157-B1. The different regions were identified based on the images of formamide (NH2CHO) and cyanodiacetylene (HC5N) lines. We discuss the observed large diversity in the molecular and organic content, both on large (3000-10,000 au) and relatively small (300-1000 au) scales. Finally, we derive upper limits to the methoxy fractional abundance in the three observed regions of the same order of magnitude of that measured in a few cold prestellar objects, namely ˜ {10}-12-10-11 with respect to H2 molecules. Based on observations carried out under project number L15AA with the IRAM-NOEMA interferometer. IRAM is supported by INSU/CNRS (France), MPG (Germany), and IGN (Spain).

Winter precipitation forecast in the European and Mediterranean regions using cluster analysis

NASA Astrophysics Data System (ADS)

Molnos, S.

2017-12-01

The European and Mediterranean climates are sensitive to large-scale circulation of the atmosphere andocean making it difficult to forecast precipitation or temperature on seasonal time-scales. In addition, theMediterranean region has been identified as a hotspot for climate change and already today a drying in theMediterranean region is observed.Thus, it is critically important to predict seasonal droughts as early as possible such that water managersand stakeholders can mitigate impacts.We developed a novel cluster-based forecast method to empirically predict winter's precipitationanomalies in European and Mediterranean regions using precursors in autumn. This approach does notonly utilizes the amplitude but also the pattern of the precursors in generating the forecast.Using a toy model we show that it achieves a better forecast skill than more traditional regression models. Furthermore, we compare our algorithm with dynamic forecast models demonstrating that our prediction method performs better in terms of time and pattern correlation in the Mediterranean and European regions.

Matching soil grid unit resolutions with polygon unit scales for DNDC modelling of regional SOC pool

NASA Astrophysics Data System (ADS)

Zhang, H. D.; Yu, D. S.; Ni, Y. L.; Zhang, L. M.; Shi, X. Z.

2015-03-01

Matching soil grid unit resolution with polygon unit map scale is important to minimize uncertainty of regional soil organic carbon (SOC) pool simulation as their strong influences on the uncertainty. A series of soil grid units at varying cell sizes were derived from soil polygon units at the six map scales of 1:50 000 (C5), 1:200 000 (D2), 1:500 000 (P5), 1:1 000 000 (N1), 1:4 000 000 (N4) and 1:14 000 000 (N14), respectively, in the Tai lake region of China. Both format soil units were used for regional SOC pool simulation with DeNitrification-DeComposition (DNDC) process-based model, which runs span the time period 1982 to 2000 at the six map scales, respectively. Four indices, soil type number (STN) and area (AREA), average SOC density (ASOCD) and total SOC stocks (SOCS) of surface paddy soils simulated with the DNDC, were attributed from all these soil polygon and grid units, respectively. Subjecting to the four index values (IV) from the parent polygon units, the variation of an index value (VIV, %) from the grid units was used to assess its dataset accuracy and redundancy, which reflects uncertainty in the simulation of SOC. Optimal soil grid unit resolutions were generated and suggested for the DNDC simulation of regional SOC pool, matching with soil polygon units map scales, respectively. With the optimal raster resolution the soil grid units dataset can hold the same accuracy as its parent polygon units dataset without any redundancy, when VIV < 1% of all the four indices was assumed as criteria to the assessment. An quadratic curve regression model y = -8.0 × 10-6x2 + 0.228x + 0.211 (R2 = 0.9994, p < 0.05) was revealed, which describes the relationship between optimal soil grid unit resolution (y, km) and soil polygon unit map scale (1:x). The knowledge may serve for grid partitioning of regions focused on the investigation and simulation of SOC pool dynamics at certain map scale.

75 FR 9157 - Proposed Information Collection; Comment Request; Alaska Region Scale and Catch Weighing...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-01

... and catch weighing requirements address performance standards designed to ensure that all catch... motherships is based on the vessel meeting a series of design criteria. Because of the wide variations in factory layout for inshore processors, NMFS requires a performance-based catch monitoring system for...

Linking a modified EPIC-based growth model (UPGM) with a component-based watershed model (AGES-W)

USDA-ARS?s Scientific Manuscript database

Agricultural models and decision support systems (DSS) for assessing water use and management are increasingly being applied to diverse geographic regions at different scales. This requires models that can simulate different crops, however, very few plant growth models are available that “easily” ...

Irrigation analysis based on long-term weather data

USDA-ARS?s Scientific Manuscript database

Irrigation-management is based upon delivery of water to a crop in the correct amount and time, and the crop’s water need is determined by calculating evapotranspiration (ET) using weather data. In 1994 an ET-network was established in the Texas High Plains to manage irrigation on a regional scale. ...

Evaluation of a Moderate Resolution, Satellite-Based Impervious Surface Map Using an Independent, High-Resolution Validation Dataset

EPA Science Inventory

Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data ...

Medical Image Tamper Detection Based on Passive Image Authentication.

PubMed

Ulutas, Guzin; Ustubioglu, Arda; Ustubioglu, Beste; V Nabiyev, Vasif; Ulutas, Mustafa

2017-12-01

Telemedicine has gained popularity in recent years. Medical images can be transferred over the Internet to enable the telediagnosis between medical staffs and to make the patient's history accessible to medical staff from anywhere. Therefore, integrity protection of the medical image is a serious concern due to the broadcast nature of the Internet. Some watermarking techniques are proposed to control the integrity of medical images. However, they require embedding of extra information (watermark) into image before transmission. It decreases visual quality of the medical image and can cause false diagnosis. The proposed method uses passive image authentication mechanism to detect the tampered regions on medical images. Structural texture information is obtained from the medical image by using local binary pattern rotation invariant (LBPROT) to make the keypoint extraction techniques more successful. Keypoints on the texture image are obtained with scale invariant feature transform (SIFT). Tampered regions are detected by the method by matching the keypoints. The method improves the keypoint-based passive image authentication mechanism (they do not detect tampering when the smooth region is used for covering an object) by using LBPROT before keypoint extraction because smooth regions also have texture information. Experimental results show that the method detects tampered regions on the medical images even if the forged image has undergone some attacks (Gaussian blurring/additive white Gaussian noise) or the forged regions are scaled/rotated before pasting.

Setting Priorities for Monitoring and Managing Non-native Plants: Toward a Practical Approach.

PubMed

Koch, Christiane; Jeschke, Jonathan M; Overbeck, Gerhard E; Kollmann, Johannes

2016-09-01

Land managers face the challenge to set priorities in monitoring and managing non-native plant species, as resources are limited and not all non-natives become invasive. Existing frameworks that have been proposed to rank non-native species require extensive information on their distribution, abundance, and impact. This information is difficult to obtain and often not available for many species and regions. National watch or priority lists are helpful, but it is questionable whether they provide sufficient information for environmental management on a regional scale. We therefore propose a decision tree that ranks species based on more simple albeit robust information, but still provides reliable management recommendations. To test the decision tree, we collected and evaluated distribution data from non-native plants in highland grasslands of Southern Brazil. We compared the results with a national list from the Brazilian Invasive Species Database for the state to discuss advantages and disadvantages of the different approaches on a regional scale. Out of 38 non-native species found, only four were also present on the national list. If management would solely rely on this list, many species that were identified as spreading based on the decision tree would go unnoticed. With the suggested scheme, it is possible to assign species to active management, to monitoring, or further evaluation. While national lists are certainly important, management on a regional scale should employ additional tools that adequately consider the actual risk of non-natives to become invasive.

Characterizing regional-scale temporal evolution of air dose rates after the Fukushima Daiichi Nuclear Power Plant accident.

PubMed

Wainwright, Haruko M; Seki, Akiyuki; Mikami, Satoshi; Saito, Kimiaki

2018-09-01

In this study, we quantify the temporal changes of air dose rates in the regional scale around the Fukushima Dai-ichi Nuclear Power Plant in Japan, and predict the spatial distribution of air dose rates in the future. We first apply the Bayesian geostatistical method developed by Wainwright et al. (2017) to integrate multiscale datasets including ground-based walk and car surveys, and airborne surveys, all of which have different scales, resolutions, spatial coverage, and accuracy. This method is based on geostatistics to represent spatial heterogeneous structures, and also on Bayesian hierarchical models to integrate multiscale, multi-type datasets in a consistent manner. We apply this method to the datasets from three years: 2014 to 2016. The temporal changes among the three integrated maps enables us to characterize the spatiotemporal dynamics of radiation air dose rates. The data-driven ecological decay model is then coupled with the integrated map to predict future dose rates. Results show that the air dose rates are decreasing consistently across the region. While slower in the forested region, the decrease is particularly significant in the town area. The decontamination has contributed to significant reduction of air dose rates. By 2026, the air dose rates will continue to decrease, and the area above 3.8 μSv/h will be almost fully contained within the non-residential forested zone. Copyright © 2018 Elsevier Ltd. All rights reserved.

Transonic wind tunnel tests of a .015 scale space shuttle booster model

NASA Technical Reports Server (NTRS)

Dennis, R. J.

1972-01-01

Details of the test program, an outline of the test procedure, and results of the investigation in tabular form are presented. The base drag reduction potential was determined at cruise conditions (M = .40) of a modified base region, with and without base bleed flow. Transonic effects and cruise control effectiveness of the new base region were also obtained. The tests were performed at Mach numbers from 0.40 to 1.10, at angles of attack from -4 to +20 degrees and at angles of sideslip from -6 to +6 degrees, all at a Reynolds number of 6.56 million per meter (2.0 million per foot).

Space based observations: A state of the art solution for spatial monitoring tropical forested watershed productivity at regional scale in developing countries

NASA Astrophysics Data System (ADS)

Mahmud, M. R.

2014-02-01

This paper presents the simplified and operational approach of mapping the water yield in tropical watershed using space-based multi sensor remote sensing data. Two main critical hydrological rainfall variables namely rainfall and evapotranspiration are being estimated by satellite measurement and reinforce the famous Thornthwaite & Mather water balance model. The satellite rainfall and ET estimates were able to represent the actual value on the ground with accuracy under considerable conditions. The satellite derived water yield had good agreement and relation with actual streamflow. A high bias measurement may result due to; i) influence of satellite rainfall estimates during heavy storm, and ii) large uncertainties and standard deviation of MODIS temperature data product. The output of this study managed to improve the regional scale of hydrology assessment in Peninsular Malaysia.

Structural evolution of photocrosslinked silk fibroin and silk fibroin-based hybrid hydrogels: A small angle and ultra-small angle scattering investigation.

PubMed

Whittaker, Jasmin L; Balu, Rajkamal; Knott, Robert; de Campo, Liliana; Mata, Jitendra P; Rehm, Christine; Hill, Anita J; Dutta, Naba K; Roy Choudhury, Namita

2018-07-15

Regenerated Bombyx mori silk fibroin (RSF) is a widely recognized protein for biomedical applications; however, its hierarchical gel structure is poorly understood. In this paper, the hierarchical structure of photocrosslinked RSF and RSF-based hybrid hydrogel systems: (i) RSF/Rec1-resilin and (ii) RSF/poly(N-vinylcaprolactam (PVCL) is reported for the first time using small-angle scattering (SAS) techniques. The structure of RSF in dilute to concentrated solution to fabricated hydrogels were characterized using small angle X-ray scattering (SAXS), small angle neutron scattering (SANS) and ultra-small angle neutron scattering (USANS) techniques. The RSF hydrogel exhibited three distinctive structural characteristics: (i) a Porod region in the length scale of 2 to 3nm due to hydrophobic domains (containing β-sheets) which exhibits sharp interfaces with the amorphous matrix of the hydrogel and the solvent, (ii) a Guinier region in the length scale of 4 to 20nm due to hydrophilic domains (containing turns and random coil), and (iii) a Porod-like region in the length scale of few micrometers due to water pores/channels exhibiting fractal-like characteristics. Addition of Rec1-resilin or PVCL to RSF and subsequent crosslinking systematically increased the nanoscale size of hydrophobic and hydrophilic domains, whereas decreased the homogeneity of pore size distribution in the microscale. The presented results have implications on the fundamental understanding of the structure-property relationship of RSF-based hydrogels. Copyright © 2018. Published by Elsevier B.V.

A wavelet analysis of scaling laws and long-memory in stock market volatility

NASA Astrophysics Data System (ADS)

Vuorenmaa, Tommi A.

2005-05-01

This paper studies the time-varying behavior of scaling laws and long-memory. This is motivated by the earlier finding that in the FX markets a single scaling factor might not always be sufficient across all relevant timescales: a different region may exist for intradaily time-scales and for larger time-scales. In specific, this paper investigates (i) if different scaling regions appear in stock market as well, (ii) if the scaling factor systematically differs from the Brownian, (iii) if the scaling factor is constant in time, and (iv) if the behavior can be explained by the heterogenuity of the players in the market and/or by intraday volatility periodicity. Wavelet method is used because it delivers a multiresolution decomposition and has excellent local adaptiviness properties. As a consequence, a wavelet-based OLS method allows for consistent estimation of long-memory. Thus issues (i)-(iv) shed light on the magnitude and behavior of a long-memory parameter, as well. The data are the 5-minute volatility series of Nokia Oyj at the Helsinki Stock Exchange around the burst of the IT-bubble. Period one represents the era of "irrational exuberance" and another the time after it. The results show that different scaling regions (i.e. multiscaling) may appear in the stock markets and not only in the FX markets, the scaling factor and the long-memory parameter are systematically different from the Brownian and they do not have to be constant in time, and that the behavior can be explained for a significant part by an intraday volatility periodicity called the New York effect. This effect was magnified by the frenzy trading of short-term speculators in the bubble period. The found stronger long-memory is also attributable to irrational exuberance.

Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

NASA Astrophysics Data System (ADS)

Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

2018-06-01

Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

Convection and electrodynamic signatures in the vicinity of a Sun-aligned arc: Results from the Polar Acceleration Regions and Convection Study (Polar ARCS)

NASA Technical Reports Server (NTRS)

Weiss, L. A.; Weber, E. J.; Reiff, P. H.; Sharber, J. R.; Winningham, J. D.; Primdahl, F.; Mikkelsen, I. S.; Seifring, C.; Wescott, Eugene M.

1994-01-01

An experimental campaign designed to study high-latitude auroral arcs was conducted in Sondre Stromfjord, Greenland, on February 26, 1987. The Polar Acceleration Regions and Convection Study (Polar ARCS) consisted of a coordinated set of ground-based, airborne, and sounding rocket measurements of a weak, sun-aligned arc system within the duskside polar cap. A rocket-borne barium release experiment, two DMSP satellite overflights, all-sky photography, and incoherent scatter radar measurements provided information on the large-scale plasma convection over the polar cap region while a second rocket instrumented with a DC magnetometer, Langmuir and electric field probes, and an electron spectrometer provided measurements of small-scale electrodynamics. The large-scale data indicate that small, sun-aligned precipitation events formed within a region of antisunward convection between the duskside auroral oval and a large sun-aligned arc further poleward. This convection signature, used to assess the relationship of the sun-aligned arc to the large-scale magnetospheric configuration, is found to be consistent with either a model in which the arc formed on open field lines on the dusk side of a bifurcated polar cap or on closed field lines threading an expanded low-latitude boundary layer, but not a model in which the polar cap arc field lines map to an expanded plasma sheet. The antisunward convection signature may also be explained by a model in which the polar cap arc formed on long field lines recently reconnected through a highly skewed plasma sheet. The small-scale measurements indicate the rocket passed through three narrow (less than 20 km) regions of low-energy (less than 100 eV) electron precipitation in which the electric and magnetic field perturbations were well correlated. These precipitation events are shown to be associated with regions of downward Poynting flux and small-scale upward and downward field-aligned currents of 1-2 micro-A/sq m. The paired field-aligned currents are associated with velocity shears (higher and lower speed streams) embedded in the region of antisunward flow.

Afforestation may have little effect on hydrological cycle over the Three-North region of China

NASA Astrophysics Data System (ADS)

Meng, S.; Xie, X.

2017-12-01

Afforestation or reforestation is generally effective to improve environmental conditions, and it may have substantial impact on hydrological cycle by increasing rainfall interception and transpiration. To combat desertification and to control dust storms, China has implemented a few Large-scale afforestation programs since 1980s, including the world's most ambitious afforestation program, the Three-North Forest Shelterbelt (TNFS) program in the arid and semiarid land areas. This afforestation plan covers about 4 million km2 (> 42%) of the land area of China. Although the TNFS program eased environmental problems in the region to some degree, the consequences of large-scale afforestation on hydrological cycles is still controversial. To identify the impact of the afforestation on hydrological cycle at regional scale, we employed a large-scale hydrological model, i.e., the Variable Infiltration Capacity (VIC) model, and satellite remote sensing data sets, i.e., leaf area index (LAI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Global LAnd Surface satellite (GLASS). The VIC modelling was forced with long-term dynamic LAI and gridded atmospheric data. We focused on the period of 2000-2015 when fewer afforestation activities implemented and the vegetation in steady growth stage in the three-north region. The results show that, despite the spatial heterogeneity, LAI in the growing season exhibits a slight increase across the three-north region, which is the contribution of the vegetation growth due to afforestation program. Evapotranspiration (ET) increased at a rate of 3.93 mm/yr over the whole region from 2000 to 2015. The spatial pattern of ET is consistent with the changes in LAI and precipitation, but this does not mean vegetation growth contributed equally. Based on factor-distinguishing simulations, we found that precipitation change has more significant influence on hydrological cycle than vegetation growth. Therefore, the afforestation practices are influential at small-catchment scale, but at regional scale, they may have little effect on the hydrological cycles. For sustainable water resource management, we should pay special attention on climate change rather than the afforestation efforts.

Landscape context for density management: implications of land ownership and ecological gradients

Treesearch

Janet L. Ohmann

2013-01-01

Density management is implemented at a local (stand) scale, but is based on conservation goals that address a broader landscape. Although regional conservation eff orts such as the Northwest Forest Plan (NWFP) focus primarily on public lands, all land ownerships and allocations contribute unique benefi ts over the regional landscape that need to be considered as...

Chemically Reactive Nitrogen Trace Species in the Planetary Boundary Layer

DTIC Science & Technology

1996-01-01

56 Biogenic NO Budget Used in the EPA Regional Oxidant Model ......... 58 Conclusions and...Regional Oxidant Model (ROM) ............................... 59 Table 2.4. Air and soil temperatures and average NO flux using W illiam s’ m odel...1985; Penkett, 1988). Yienger and Levy (1995) developed an empirically based model to estimate soil NOx emissions on a global scale. They have reported

Regional synchroneity in fire regimes of western Oregon and Washington, USA.

Treesearch

P.J. Weisberg; F.J. Swanson

2003-01-01

For much of the world's forested area, the history of fire has significant implications for understanding forest dynamics over stand to regional scales. We analyzed temporal patterns of area burned at 25-year intervals over a 600-year period, using 10 treering-based fire history studies located west of the crest of the Cascade Range in the Pacific Northwest (PNW...

Watershed management and organizational dynamics: nationwide findings and regional variation

USGS Publications Warehouse

Clark, B.T.; Burkardt, N.; King, M.D.

2005-01-01

Recent attention has focused on resource management initiatives at the watershed scale with emphasis on collaborative, locally driven, and decentralized institutional arrangements. Existing literature on limited selections of well-established watershed-based organizations has provided valuable insights. The current research extends this focus by including a broad survey of watershed organizations from across the United States as a means to estimate a national portrait. Organizational characteristics include year of formation, membership size and composition, budget, guiding principles, and mechanisms of decision-making. These characteristics and the issue concerns of organizations are expected to vary with respect to location. Because this research focuses on organizations that are place based and stakeholder driven, the forces driving them are expected to differ across regions of the country. On this basis of location, we suggest basic elements for a regional assessment of watershed organizations to channel future research and to better approximate the organizational dynamics, issue concerns, and information needs unique to organizations across the country. At the broadest level, the identification of regional patterns or organizational similarities may facilitate the linkage among organizations to coordinate their actions at the much broader river basin or ecosystem scale.

Studies on the dynamic stability of an axially moving nanobeam based on the nonlocal strain gradient theory

NASA Astrophysics Data System (ADS)

Wang, Jing; Shen, Huoming; Zhang, Bo; Liu, Juan

2018-06-01

In this paper, we studied the parametric resonance issue of an axially moving viscoelastic nanobeam with varying velocity. Based on the nonlocal strain gradient theory, we established the transversal vibration equation of the axially moving nanobeam and the corresponding boundary condition. By applying the average method, we obtained a set of self-governing ordinary differential equations when the excitation frequency of the moving parameters is twice the intrinsic frequency or near the sum of certain second-order intrinsic frequencies. On the plane of parametric excitation frequency and excitation amplitude, we can obtain the instability region generated by the resonance, and through numerical simulation, we analyze the influence of the scale effect and system parameters on the instability region. The results indicate that the viscoelastic damping decreases the resonance instability region, and the average velocity and stiffness make the instability region move to the left- and right-hand sides. Meanwhile, the scale effect of the system is obvious. The nonlocal parameter exhibits not only the stiffness softening effect but also the damping weakening effect, while the material characteristic length parameter exhibits the stiffness hardening effect and damping reinforcement effect.

Watershed management and organizational dynamics: nationwide findings and regional variation.

PubMed

Clark, Brad T; Burkardt, Nina; King, Dawn

2005-08-01

Recent attention has focused on resource management initiatives at the watershed scale with emphasis on collaborative, locally driven, and decentralized institutional arrangements. Existing literature on limited selections of well-established watershed-based organizations has provided valuable insights. The current research extends this focus by including a broad survey of watershed organizations from across the United States as a means to estimate a national portrait. Organizational characteristics include year of formation, membership size and composition, budget, guiding principles, and mechanisms of decision-making. These characteristics and the issue concerns of organizations are expected to vary with respect to location. Because this research focuses on organizations that are place based and stakeholder driven, the forces driving them are expected to differ across regions of the country. On this basis of location, we suggest basic elements for a regional assessment of watershed organizations to channel future research and to better approximate the organizational dynamics, issue concerns, and information needs unique to organizations across the country. At the broadest level, the identification of regional patterns or organizational similarities may facilitate the linkage among organizations to coordinate their actions at the much broader river basin or ecosystem scale.

Geologic map of the Nepenthes Planum Region, Mars

USGS Publications Warehouse

Skinner, James A.; Tanaka, Kenneth L.

2018-03-26

This map product contains a map sheet at 1:1,506,000 scale that shows the geology of the Nepenthes Planum region of Mars, which is located between the cratered highlands that dominate the southern hemisphere and the less-cratered sedimentary plains that dominate the northern hemisphere.  The map region contains cone- and mound-shaped landforms as well as lobate materials that are morphologically similar to terrestrial igneous or mud vents and flows. This map is part of an informal series of small-scale (large-area) maps aimed at refining current understanding of the geologic units and structures that make up the highland-to-lowland transition zone. The map base consists of a controlled Thermal Emission Imaging System (THEMIS) daytime infrared image mosaic (100 meters per pixel resolution) supplemented by a Mars Orbiter Laser Altimeter (MOLA) digital elevation model (463 meters per pixel resolution). The map includes a Description of Map Units and a Correlation of Map Units that describes and correlates units identified across the entire map region. The geologic map was assembled using ArcGIS software by Environmental Systems Research Institute (http://www.esri.com). The ArcGIS project, geodatabase, base map, and all map components are included online as supplemental data.

Crowd counting via region based multi-channel convolution neural network

NASA Astrophysics Data System (ADS)

Cao, Xiaoguang; Gao, Siqi; Bai, Xiangzhi

2017-11-01

This paper proposed a novel region based multi-channel convolution neural network architecture for crowd counting. In order to effectively solve the perspective distortion in crowd datasets with a great diversity of scales, this work combines the main channel and three branch channels. These channels extract both the global and region features. And the results are used to estimate density map. Moreover, kernels with ladder-shaped sizes are designed across all the branch channels, which generate adaptive region features. Also, branch channels use relatively deep and shallow network to achieve more accurate detector. By using these strategies, the proposed architecture achieves state-of-the-art performance on ShanghaiTech datasets and competitive performance on UCF_CC_50 datasets.

Observed evolution of drought episodes assessed with the Standardized Precipitation Evapotranspiration Index (SPEI) over the Czech Republic

NASA Astrophysics Data System (ADS)

Potop, V.; Boroneana, C.; Mozny, M.; Stepanek, P.; Skalak, P.

2012-04-01

This paper investigates the spatial and temporal evolution of drought episodes assessed with the Standardized Precipitation Evapotranspiration Index (SPEI) over the Czech Republic. The SPEI were calculated from monthly records of mean temperature and precipitation totals using a dense network of 183 climatological stations for the period 1961-2010. The SPEI were calculated with various lags, 1, 3, 6, 12 and 24 months. The drought at these time scales is relevant for agricultural, hydrological and socio-economic impact, respectively. The study refers at the warm season of the year (April to September). The principal modes of variability of these five time scale SPEI were identified using the analysis of Empirical Orthogonal Functions (EOF). The explained variance of the leading EOF ranges between 71 and 61% as the time scale for calculating the SPEI increases from 1 month to 24 months. The explained variance of EOF2 and EOF3 ranges between 5 to 9% and 4 to 6%, respectively, as the SPEI is calculated for 1 to 24 months. Based on the spatial distribution of the EOF2 and EOF3 for all time scales of SPEI, which correspond to some extend to a regionalization previously used in other studies, we identified three climatically homogeneous regions, corresponding to the altitudes below 400 m, between 401 and 700 m and, above 700 m. These regions correspond to different land use types with mostly intensive agriculture, less intensive agriculture and limited agricultural production and mostly forested, respectively. For these three regions the frequency distribution of the SPEI values in 7 classes of drought category (%) were calculated based on station records in each region. The normal conditions represent around 65% out of the total values of SPEI for all times scales, in all three regions, while moderate drought and moderate wet conditions are almost equally distributed around 10.5 %. Differences in extremely dry conditions (5%) compared to extremely wet conditions (1.5 %) were observed when increasing the SPEI timescales. The drought is classified as local when covers up to 10% of the territory of the Czech Republic, widespread when covers 11-30% of the territory, very widespread when covers 31-50% of the territory and most extended when covers more than 50% of the country territory. We gratefully acknowledge the support of the Ministry of Education, Youth and Sports for projects OC10010.

Evaluation of different rainfall products over India for the summer monsoon

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mitra, Ashis; Turner, Andrew; Collins, Mathew; AchutoRao, Krishna

2015-04-01

Summer rainfall over India forms an integral part of the Asian monsoon, which plays a key role in the global water cycle and climate system through coupled atmospheric and oceanic processes. Accurate prediction of Indian summer monsoon rainfall and its variability at various spatiotemporal scales are crucial for agriculture, water resources and hydroelectric-power sectors. Reliable rainfall observations are very important for verification of numerical model outputs and model development. However, high spatiotemporal variability of rainfall makes it difficult to measure adequately with ground-based instruments over a large region of various surface types from deserts to oceans. A number of multi-satellite rainfall products are available to users at different spatial and temporal scales. Each rainfall product has some advantages as well as limitations, hence it is essential to find a suitable region-specific data set among these rainfall products for a particular user application, such as water resources, agricultural modelling etc. In this study, we examine seasonal-mean and daily rainfall datasets for monsoon model validation. First, six multi-satellite and gauge-only rainfall products were evaluated over India at seasonal scale for 27 (JJAS 1979-2005) summer monsoon seasons against gridded 0.5-degree IMD gauge-based rainfall. Various skill metrics are computed to assess the potential of these data sets in representation of large-scale monsoon rainfall at all-India and sub-regional scales. Among the gauge-only data sets, APHRODITE and GPCC appear to outperform the others whereas GPCP is better than CMAP in the merged multi-satellite category. However, there are significant differences among these data sets indicating uncertainty in the observed rainfall over this region, with important implications for the evaluation of model simulations. At the daily scale, TRMM TMPA-3B42 is one of the best available products and is widely used for various hydro-meteorological applications. The existing version 6 (V6) products of TRMM underwent major changes and version 7 (V7) products were released in late 2012, and we compare these to the IMD daily gridded data over the 1998-2010 period. We show a clear improvement in V7 over V6 in the South Asian monsoon region using various skill metrics. Over typical monsoon rainfall zones, biases are improved by 5-10% in V7 over higher-rainfall regions. These results will help users to select appropriate rainfall product for their application. With the recent launch of the GPM Core Observatory, the release of a more advanced high-resolution multi-satellite rainfall product is expected soon.

Global daily reference evapotranspiration modeling and evaluation

USGS Publications Warehouse

Senay, G.B.; Verdin, J.P.; Lietzow, R.; Melesse, Assefa M.

2008-01-01

Accurate and reliable evapotranspiration (ET) datasets are crucial in regional water and energy balance studies. Due to the complex instrumentation requirements, actual ET values are generally estimated from reference ET values by adjustment factors using coefficients for water stress and vegetation conditions, commonly referred to as crop coefficients. Until recently, the modeling of reference ET has been solely based on important weather variables collected from weather stations that are generally located in selected agro-climatic locations. Since 2001, the National Oceanic and Atmospheric Administration’s Global Data Assimilation System (GDAS) has been producing six-hourly climate parameter datasets that are used to calculate daily reference ET for the whole globe at 1-degree spatial resolution. The U.S. Geological Survey Center for Earth Resources Observation and Science has been producing daily reference ET (ETo) since 2001, and it has been used on a variety of operational hydrological models for drought and streamflow monitoring all over the world. With the increasing availability of local station-based reference ET estimates, we evaluated the GDAS-based reference ET estimates using data from the California Irrigation Management Information System (CIMIS). Daily CIMIS reference ET estimates from 85 stations were compared with GDAS-based reference ET at different spatial and temporal scales using five-year daily data from 2002 through 2006. Despite the large difference in spatial scale (point vs. ∼100 km grid cell) between the two datasets, the correlations between station-based ET and GDAS-ET were very high, exceeding 0.97 on a daily basis to more than 0.99 on time scales of more than 10 days. Both the temporal and spatial correspondences in trend/pattern and magnitudes between the two datasets were satisfactory, suggesting the reliability of using GDAS parameter-based reference ET for regional water and energy balance studies in many parts of the world. While the study revealed the potential of GDAS ETo for large-scale hydrological applications, site-specific use of GDAS ETo in complex hydro-climatic regions such as coastal areas and rugged terrain may require the application of bias correction and/or disaggregation of the GDAS ETo using downscaling techniques.

The DRAGON scale concept and results for remote sensing of aerosol properties

NASA Astrophysics Data System (ADS)

Holben, B. N.; Eck, T. F.; Schafer, J.; Giles, D. M.; Kim, J.; Sano, I.; Mukai, S.; Kim, Y. J.; Reid, J. S.; Pickering, K. E.; Crawford, J. H.; Smirnov, A.; Sinyuk, A.; Slutsker, I.; Sorokin, M.; Rodriguez, J.; Liew, S.; Trevino, N.; Lim, H.; Lefer, B. L.; Nadkarni, R.; Macke, A.; Kinne, S. A.; Anderson, B. E.; Russell, P. B.; Maring, H. B.; Welton, E. J.; da Silva, A.; Toon, O. B.; Redemann, J.

2013-12-01

Aerosol processes occur at microscales but are typically observed and reported at continental to global scales. Often observable aerosol processes that have significant anthropogenic impact occur on spatial scales of tens to a few hundred km, representative of convective cloud processing, urban/megacity sources, anthropogenic burning and natural wildfires, dry lakebed dust sources etc. Historically remote sensing of aerosols has relied on relatively coarse temporal and spatial resolution satellite observations or high temporal resolution point observations from ground-based monitoring sites from networks such as AERONET, SKYNET, MPLNET and many other surface observation platforms. Airborne remote and in situ observations combined with assimilation models were/are to be the mesoscale link between the ground- and space-based RS scales. However clearly the in situ and ground-based RS characterizations of aerosols require a convergence of thought, parameterization and actual scale measurements in order to advance this goal. This has been served by periodic multidisciplinary field campaigns yet only recently has a concerted effort been made to establish these ground-based networks in an effort to capture the mesoscale processes through measurement programs such as DISCOVER AQ and NASA AERONET's effort to foster such measurements and analysis through the Distributed Regional Aerosol Gridded Observation Networks (DRAGON), short term meso-networks, with partners in Asia and Europe and N. America. This talk will review the historical need for such networks and discuss some of the results and in some cases unexpected findings from the eight DRAGON campaigns conducted the last several years. Emphasis will be placed on the most recent DISCOVER AQ campaign conducted in Houston TX and the synergism with a regional to global network plan through the SEAC4RS US campaign.

Downscaling Global Land Cover Projections from an Integrated Assessment Model for Use in Regional Analyses: Results and Evaluation for the US from 2005 to 2095

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

West, Tristram O.; Le Page, Yannick LB; Huang, Maoyi

2014-06-05

Projections of land cover change generated from Integrated Assessment Models (IAM) and other economic-based models can be applied for analyses of environmental impacts at subregional and landscape scales. For those IAM and economic models that project land use at the sub-continental or regional scale, these projections must be downscaled and spatially distributed prior to use in climate or ecosystem models. Downscaling efforts to date have been conducted at the national extent with relatively high spatial resolution (30m) and at the global extent with relatively coarse spatial resolution (0.5 degree).

Coniferous canopy BRF simulation based on 3-D realistic scene.

PubMed

Wang, Xin-Yun; Guo, Zhi-Feng; Qin, Wen-Han; Sun, Guo-Qing

2011-09-01

It is difficulties for the computer simulation method to study radiation regime at large-scale. Simplified coniferous model was investigated in the present study. It makes the computer simulation methods such as L-systems and radiosity-graphics combined method (RGM) more powerful in remote sensing of heterogeneous coniferous forests over a large-scale region. L-systems is applied to render 3-D coniferous forest scenarios, and RGM model was used to calculate BRF (bidirectional reflectance factor) in visible and near-infrared regions. Results in this study show that in most cases both agreed well. Meanwhile at a tree and forest level, the results are also good.

Coniferous Canopy BRF Simulation Based on 3-D Realistic Scene

NASA Technical Reports Server (NTRS)

Wang, Xin-yun; Guo, Zhi-feng; Qin, Wen-han; Sun, Guo-qing

2011-01-01

It is difficulties for the computer simulation method to study radiation regime at large-scale. Simplified coniferous model was investigate d in the present study. It makes the computer simulation methods such as L-systems and radiosity-graphics combined method (RGM) more powerf ul in remote sensing of heterogeneous coniferous forests over a large -scale region. L-systems is applied to render 3-D coniferous forest scenarios: and RGM model was used to calculate BRF (bidirectional refle ctance factor) in visible and near-infrared regions. Results in this study show that in most cases both agreed well. Meanwhiie at a tree and forest level. the results are also good.

Status of the Majorana Demonstrator

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

Cuesta, C.; Abgrall, N.; Arnquist, Isaac J.

2015-06-09

The Majorana Collaboration is constructing the Majorana Demonstrator, an ultra-low background, 40-kg modular high purity Ge detector array to search for neutrinoless double-beta decay in 76Ge. In view of the next generation of tonne-scale Ge-based neutrinoless double-beta decay searches that will probe the neutrino mass scale in the inverted hierarchy region, a major goal of the Demonstrator is to demonstrate a path forward to achieving a background rate at or below 1 count/tonne/year in the 4 keV region of interest around the Q-value at 2039 keV. The current status of the Demonstrator is discussed, as are plans for its completion.

Global Albedo Variations on Mars from Recent MRO/MARCI and Other Space-Based Observations

NASA Astrophysics Data System (ADS)

Bell, J. F., III; Wellington, D. F.

2017-12-01

Dramatic changes in Mars surface albedo have been quantified by telescopic, orbital, and surface-based observations over the last 40 years. These changes provide important inputs for global and mesoscale climate models, enabling characterization of seasonal and secular variations in the distribution of mobile surface materials (dust, sand) in the planet's current climate regime. Much of the modern record of dust storms and albedo changes comes from synoptic-scale global imaging from the Viking Orbiter, Mars Global Surveyor (MGS), Hubble Space Telescope (HST), and Mars Reconnaissance Orbiter (MRO) missions, as well as local-scale observations from long-lived surface platforms like the Spirit and Opportunity rovers. Here we focus on the substantial time history of global-scale images acquired from the MRO Mars Color Imager (MARCI). MARCI is a wide-angle multispectral imager that acquires daily coverage of most of the surface at up to 1 km/pixel. MARCI has been in orbit since 2006, providing six Mars years of continuous surface and atmospheric observations, and building on the nearly five previous Mars years of global-scale imaging from the MGS Mars Orbiter Camera Wide Angle (MOC/WA) imager, which operated from 1997 to 2006. While many of the most significant MARCI-observed changes in the surface albedo are the result of large dust storms, other regions experience seasonal darkening events that repeat with different degrees of annual regularity. Some of these are associated with local dust storms, while for others, frequent surface changes take place with no associated evidence for dust storms, suggesting action by seasonally-variable winds and/or small-scale storms/dust devils too small to resolve. Discrete areas of dramatic surface changes across widely separated regions of Tharsis and in portions of Solis Lacus and Syrtis Major are among the regions where surface changes have been observed without a direct association to specific detectable dust storm events. Deposition following the annual southern summer dusty season plays a significant role in maintaining the cyclic nature of these changes. These and other historical observations also show that major regional or global-scale dust storms produce unique changes that may require several Mars years to reverse.

Regional and climate forcing on forage fish and apex predators in the California Current: new insights from a fully coupled ecosystem model.

NASA Astrophysics Data System (ADS)

Fiechter, J.; Rose, K.; Curchitser, E. N.; Huckstadt, L. A.; Costa, D. P.; Hedstrom, K.

2016-12-01

A fully coupled ecosystem model is used to describe the impact of regional and climate variability on changes in abundance and distribution of forage fish and apex predators in the California Current Large Marine Ecosystem. The ecosystem model consists of a biogeochemical submodel (NEMURO) embedded in a regional ocean circulation submodel (ROMS), and both coupled with a multi-species individual-based submodel for two forage fish species (sardine and anchovy) and one apex predator (California sea lion). Sardine and anchovy are specifically included in the model as they exhibit significant interannual and decadal variability in population abundances, and are commonly found in the diet of California sea lions. Output from the model demonstrates how regional-scale (i.e., upwelling intensity) and basin-scale (i.e., PDO and ENSO signals) physical processes control species distributions and predator-prey interactions on interannual time scales. The results also illustrate how variability in environmental conditions leads to the formation of seasonal hotspots where prey and predator spatially overlap. While specifically focused on sardine, anchovy and sea lions, the modeling framework presented here can provide new insights into the physical and biological mechanisms controlling trophic interactions in the California Current, or other regions where similar end-to-end ecosystem models may be implemented.

Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2017-03-01

We propose using multi-scale image textures to investigate links between neuroanatomical regions and clinical variables in MRI. Texture features are derived at multiple scales of resolution based on the Laplacian-of-Gaussian (LoG) filter. Three quantifier functions (Average, Standard Deviation and Entropy) are used to summarize texture statistics within standard, automatically segmented neuroanatomical regions. Significance tests are performed to identify regional texture differences between ASD vs. TDC and male vs. female groups, as well as correlations with age (corrected p < 0.05). The open-access brain imaging data exchange (ABIDE) brain MRI dataset is used to evaluate texture features derived from 31 brain regions from 1112 subjects including 573 typically developing control (TDC, 99 females, 474 males) and 539 Autism spectrum disorder (ASD, 65 female and 474 male) subjects. Statistically significant texture differences between ASD vs. TDC groups are identified asymmetrically in the right hippocampus, left choroid-plexus and corpus callosum (CC), and symmetrically in the cerebellar white matter. Sex-related texture differences in TDC subjects are found in primarily in the left amygdala, left cerebellar white matter, and brain stem. Correlations between age and texture in TDC subjects are found in the thalamus-proper, caudate and pallidum, most exhibiting bilateral symmetry.

Field-scale and Regional Variability in Evapotranspiration over Crops in California using Eddy Covariance and Surface Renewal

NASA Astrophysics Data System (ADS)

Kent, E. R.; Clay, J. M.; Leinfelder-Miles, M.; Lambert, J. J.; Little, C.; Monteiro, R. O. C.; Monteiro, P. F. C.; Shapiro, K.; Rice, S.; Snyder, R. L.; Daniele, Z.; Paw U, K. T.

2016-12-01

Evapotranspiration (ET) estimated using a single crop coefficient and a grass reference largely ignores variability due to heterogeneity in microclimate, soils, and crop management. We employ a relatively low cost energy balance residual method using surface renewal and eddy covariance measurements to continuously estimate half-hourly and daily ET across more than 15 fields and orchards spanning four crops and two regions of California. In the Sacramento-San Joaquin River Delta, measurements were taken in corn, pasture, and alfalfa fields, with 4-5 stations in each crop type spread across the region. In the Southern San Joaquin Valley, measurements were taken in three different pistachio orchards, with one orchard having six stations instrumented to examine salinity-induced heterogeneity. We analyze field-scale and regional variability in ET and measured surface energy balance components. Cross comparisons between the eddy covariance and the surface renewal measurements confirm the robustness of the surface renewal method. A hybrid approach in which remotely sensed net radiation is combined with in situ measurements of sensible heat flux is also investigated. This work will provide ground-truth data for satellite and aerial-based ET estimates and will inform water management at the field and regional scales.

Global analysis of approaches for deriving total water storage changes from GRACE satellites and implications for groundwater storage change estimation

NASA Astrophysics Data System (ADS)

Long, D.; Scanlon, B. R.; Longuevergne, L.; Chen, X.

2015-12-01

Increasing interest in use of GRACE satellites and a variety of new products to monitor changes in total water storage (TWS) underscores the need to assess the reliability of output from different products. The objective of this study was to assess skills and uncertainties of different approaches for processing GRACE data to restore signal losses caused by spatial filtering based on analysis of 1°×1° grid scale data and basin scale data in 60 river basins globally. Results indicate that scaling factors from six land surface models (LSMs), including four models from GLDAS-1 (Noah 2.7, Mosaic, VIC, and CLM 2.0), CLM 4.0, and WGHM, are similar over most humid, sub-humid, and high-latitude regions but can differ by up to 100% over arid and semi-arid basins and areas with intensive irrigation. Large differences in TWS anomalies from three processing approaches (scaling factor, additive, and multiplicative corrections) were found in arid and semi-arid regions, areas with intensive irrigation, and relatively small basins (e.g., ≤ 200,000 km2). Furthermore, TWS anomaly products from gridded data with CLM4.0 scaling factors and the additive correction approach more closely agree with WGHM output than the multiplicative correction approach. Estimation of groundwater storage changes using GRACE satellites requires caution in selecting an appropriate approach for restoring TWS changes. A priori ground-based data used in forward modeling can provide a powerful tool for explaining the distribution of signal gains or losses caused by low-pass filtering in specific regions of interest and should be very useful for more reliable estimation of groundwater storage changes using GRACE satellites.

Scale problems in assessment of hydrogeological parameters of groundwater flow models

NASA Astrophysics Data System (ADS)

Nawalany, Marek; Sinicyn, Grzegorz

2015-09-01

An overview is presented of scale problems in groundwater flow, with emphasis on upscaling of hydraulic conductivity, being a brief summary of the conventional upscaling approach with some attention paid to recently emerged approaches. The focus is on essential aspects which may be an advantage in comparison to the occasionally extremely extensive summaries presented in the literature. In the present paper the concept of scale is introduced as an indispensable part of system analysis applied to hydrogeology. The concept is illustrated with a simple hydrogeological system for which definitions of four major ingredients of scale are presented: (i) spatial extent and geometry of hydrogeological system, (ii) spatial continuity and granularity of both natural and man-made objects within the system, (iii) duration of the system and (iv) continuity/granularity of natural and man-related variables of groundwater flow system. Scales used in hydrogeology are categorised into five classes: micro-scale - scale of pores, meso-scale - scale of laboratory sample, macro-scale - scale of typical blocks in numerical models of groundwater flow, local-scale - scale of an aquifer/aquitard and regional-scale - scale of series of aquifers and aquitards. Variables, parameters and groundwater flow equations for the three lowest scales, i.e., pore-scale, sample-scale and (numerical) block-scale, are discussed in detail, with the aim to justify physically deterministic procedures of upscaling from finer to coarser scales (stochastic issues of upscaling are not discussed here). Since the procedure of transition from sample-scale to block-scale is physically well based, it is a good candidate for upscaling block-scale models to local-scale models and likewise for upscaling local-scale models to regional-scale models. Also the latest results in downscaling from block-scale to sample scale are briefly referred to.

Soil-geographical regionalization as a basis for digital soil mapping: Karelia case study

NASA Astrophysics Data System (ADS)

Krasilnikov, P.; Sidorova, V.; Dubrovina, I.

2010-12-01

Recent development of digital soil mapping (DSM) allowed improving significantly the quality of soil maps. We tried to make a set of empirical models for the territory of Karelia, a republic at the North-East of the European territory of Russian Federation. This territory was selected for the pilot study for DSM for two reasons. First, the soils of the region are mainly monogenetic; thus, the effect of paleogeographic environment on recent soils is reduced. Second, the territory was poorly mapped because of low agricultural development: only 1.8% of the total area of the republic is used for agriculture and has large-scale soil maps. The rest of the territory has only small-scale soil maps, compiled basing on the general geographic concepts rather than on field surveys. Thus, the only solution for soil inventory was the predictive digital mapping. The absence of large-scaled soil maps did not allow data mining from previous soil surveys, and only empirical models could be applied. For regionalization purposes, we accepted the division into Northern and Southern Karelia, proposed in the general scheme of soil regionalization of Russia; boundaries between the regions were somewhat modified. Within each region, we specified from 15 (Northern Karelia) to 32 (Southern Karelia) individual soilscapes and proposed soil-topographic and soil-lithological relationships for every soilscape. Further field verification is needed to adjust the models.

Upscaling Empirically Based Conceptualisations to Model Tropical Dominant Hydrological Processes for Historical Land Use Change

NASA Astrophysics Data System (ADS)

Toohey, R.; Boll, J.; Brooks, E.; Jones, J.

2009-12-01

Surface runoff and percolation to ground water are two hydrological processes of concern to the Atlantic slope of Costa Rica because of their impacts on flooding and drinking water contamination. As per legislation, the Costa Rican Government funds land use management from the farm to the regional scale to improve or conserve hydrological ecosystem services. In this study, we examined how land use (e.g., forest, coffee, sugar cane, and pasture) affects hydrological response at the point, plot (1 m2), and the field scale (1-6ha) to empirically conceptualize the dominant hydrological processes in each land use. Using our field data, we upscaled these conceptual processes into a physically-based distributed hydrological model at the field, watershed (130 km2), and regional (1500 km2) scales. At the point and plot scales, the presence of macropores and large roots promoted greater vertical percolation and subsurface connectivity in the forest and coffee field sites. The lack of macropores and large roots, plus the addition of management artifacts (e.g., surface compaction and a plough layer), altered the dominant hydrological processes by increasing lateral flow and surface runoff in the pasture and sugar cane field sites. Macropores and topography were major influences on runoff generation at the field scale. Also at the field scale, antecedent moisture conditions suggest a threshold behavior as a temporal control on surface runoff generation. However, in this tropical climate with very intense rainstorms, annual surface runoff was less than 10% of annual precipitation at the field scale. Significant differences in soil and hydrological characteristics observed at the point and plot scales appear to have less significance when upscaled to the field scale. At the point and plot scales, percolation acted as the dominant hydrological process in this tropical environment. However, at the field scale for sugar cane and pasture sites, saturation-excess runoff increased as irrigation intensity and duration (e.g., quantity) increased. Upscaling our conceptual models to the watershed and regional scales, historical data (1970-2004) was used to investigate whether dominant hydrological processes changed over time due to land use change. Preliminary investigations reveal much higher runoff coefficients (<30%) at the larger watershed scales. The increase in importance of runoff at the larger geographic scales suggests an emerging process and process non-linearity between the smaller and larger scales. Upscaling is an important and useful concept when investigating catchment response using the tools of field work and/or physically distributed hydrological modeling.

Indicators of wetland condition for the Prairie Pothole Region of the United States

USGS Publications Warehouse

Guntenspergen, Glenn R.; Peterson, S.A.; Leibowitz, S.G.; Cowardin, L.M.

2002-01-01

We describe a study designed to evaluate the performance ofwetland condition indicators of the Prairie Pothole Region (PPR)of the north central United States. Basin and landscape scaleindicators were tested in 1992 and 1993 to determine theirability to discriminate between the influences of grasslanddominated and cropland dominated landscapes in the PPR. Pairedplots were selected from each of the major regions of the PPR.Among the landscape scale indicators tested, those most capableof distinguishing between the two landscapes were: 1) frequencyof drained wetland basins, 2) total length of drainage ditch perplot, 3) amount of exposed soil in the upland subject to erosion,4) indices of change in area of wetland covered by water, and5) number of breeding duck pairs. Basin scale indicators includingsoil phosphorus concentrations and invertebrate taxa richnessshowed some promise; however, plant species richness was the onlystatistically significant basin scale indicator distinguishinggrassland dominated from cropland dominated landscapes. Althoughour study found a number of promising candidate indicators, oneof our conclusions is that basin scale indicators present anumber of implementation problems, including: skill levelrequirements, site access denials, and recession of site accessby landowners. Alternatively, we suggest that the use oflandscape indicators based on remote sensing can be an effectivemeans of assessing wetland integrity.

Shoreline changes and its impact on archaeological sites in West Greenland

NASA Astrophysics Data System (ADS)

Fenger-Nielsen, R.; Kroon, A.; Elberling, B.; Hollesen, J.

2017-12-01

Coastal erosion is regarded as a major threat to archaeological sites in the Arctic region. The problem arises because the predominantly marine-focused lifeways of Arctic people means that the majority of archaeological sites are found near the coast. On a Pan-Arctic scale, coastal erosion is often explained by long-term processes such as sea level rise, lengthening of open water periods due to a decline in sea ice, and a predicted increase in the frequency of major storms. However, on a local scale other short-term processes may be important parameters determining the coastal development. In this study, we focus on the Nuuk fjord system in West Greenland, which has been inhabited over the past 4000 years by different cultures and holds around 260 registered archaeological settlements. The fjord is characterized by its large branching of narrow deep-water and well-shaded water bodies, where tidal processes and local sources of sediment supply by rivers are observed to be the dominant factors determining the coastal development. We present a regional model showing the vulnerability of the shoreline and archeological sites due to coastal processes. The model is based on a) levelling surveys and historical aerial photographs of nine specific sites distributed in the region, b) water level measurements at three sites representing the inner-, middle- and outer fjord system, c) aerial photographs, satellite images and meteorological data of the entire region used to up-scale our local information at a specific settlement scale towards a regional scale. This deals with spatial and temporal variability in erosion and accumulation patterns along the shores in fjords and open seas.

Regional-scale comparison of the effects of lakes and reservoirs versus streams on water quality

NASA Astrophysics Data System (ADS)

Schmadel, N. M.; Harvey, J. W.; Alexander, R. B.; Schwarz, G. E.; Moore, R. B.; Gomez-Velez, J. D.; Scott, D.; Boyer, E. W.

2017-12-01

Recent physically-based modeling at regional scales has revealed that the potential for biogeochemical transformations of nitrogen—such as denitrification—along a fluvial network may be dominated by hyporheic exchange. However, fluvial networks are comprised of a mosaic of water body types from headwaters to coasts, each potentially playing a different role in water quality. For example, depending on conditions, streams or ponded waters (lakes, reservoirs) may disproportionately act as biogeochemical hotspots. Because downstream water quality reflects an accumulation or blending of processes, it is not clear how ponded waters that vary in number and location across a network influence downstream water quality. Here, we quantified the effects of ponded waters along fluvial networks on the fate of nitrogen in the Northeastern and Mid-Atlantic regions of the United States. We used a spatially referenced model calibrated to land use and water quality data and considered both the number and location of ponded waters across the regions. We experimentally modeled the replacement of nearly 30,000 ponded waters with streams using corresponding estimates of hydraulic geometry and nitrogen removal, thereby providing a direct comparison of the role of ponded waters versus the role of streams with regard to nitrogen removal. We found that pond size, density (total pond area to drainage area), and position within a network were all important factors. These findings complement field measurements and reach-scale modeling by upscaling to reveal cumulative effects. This regional-scale modeling of ponded waters is useful toward developing better strategies for prioritizing creation of new reservoirs or removal of dams, or informing stream restoration at ecologically-relevant scales. This research is a product of the John Wesley Powell Center River Corridor Working Group. powellcenter.usgs.gov/view-project

Multi-scale linkages of winter drought variability to ENSO and the Arctic Oscillation: A case study in Shaanxi, North China

NASA Astrophysics Data System (ADS)

Liu, Zhiyong; Zhang, Xin; Fang, Ruihong

2018-02-01

Understanding the potential connections between climate indices such as the El Niño-Southern Oscillation (ENSO) and Arctic Oscillation (AO) and drought variability will be beneficial for making reasonable predictions or assumptions about future regional droughts, and provide valuable information to improve water resources planning and design for specific regions of interest. This study is to examine the multi-scale relationships between winter drought variability over Shaanxi (North China) and both ENSO and AO during the period 1960-2009. To accomplish this, we first estimated winter dryness/wetness conditions over Shaanxi based on the self-calibrating Palmer drought severity index (PDSI). Then, we identified the spatiotemporal variability of winter dryness/wetness conditions in the study area by using the empirical orthogonal function (EOF). Two primary sub-regions of winter dryness/wetness conditions across Shaanxi were identified. We further examined the periodical oscillations of dryness/wetness conditions and the multi-scale relationships between dryness/wetness conditions and both ENSO and AO in winter using wavelet analysis. The results indicate that there are inverse multi-scale relations between winter dryness/wetness conditions and ENSO (according to the wavelet coherence) for most of the study area. Moreover, positive multi-scale relations between winter dryness/wetness conditions and AO are mainly observed. The results could be beneficial for making reasonable predictions or assumptions about future regional droughts and provide valuable information to improve water resources planning and design within this study area. In addition to the current study area, this study may also offer a useful reference for other regions worldwide with similar climate conditions.

Large-scale coherent structures of suspended dust concentration in the neutral atmospheric surface layer: A large-eddy simulation study

NASA Astrophysics Data System (ADS)

Zhang, Yangyue; Hu, Ruifeng; Zheng, Xiaojing

2018-04-01

Dust particles can remain suspended in the atmospheric boundary layer, motions of which are primarily determined by turbulent diffusion and gravitational settling. Little is known about the spatial organizations of suspended dust concentration and how turbulent coherent motions contribute to the vertical transport of dust particles. Numerous studies in recent years have revealed that large- and very-large-scale motions in the logarithmic region of laboratory-scale turbulent boundary layers also exist in the high Reynolds number atmospheric boundary layer, but their influence on dust transport is still unclear. In this study, numerical simulations of dust transport in a neutral atmospheric boundary layer based on an Eulerian modeling approach and large-eddy simulation technique are performed to investigate the coherent structures of dust concentration. The instantaneous fields confirm the existence of very long meandering streaks of dust concentration, with alternating high- and low-concentration regions. A strong negative correlation between the streamwise velocity and concentration and a mild positive correlation between the vertical velocity and concentration are observed. The spatial length scales and inclination angles of concentration structures are determined, compared with their flow counterparts. The conditionally averaged fields vividly depict that high- and low-concentration events are accompanied by a pair of counter-rotating quasi-streamwise vortices, with a downwash inside the low-concentration region and an upwash inside the high-concentration region. Through the quadrant analysis, it is indicated that the vertical dust transport is closely related to the large-scale roll modes, and ejections in high-concentration regions are the major mechanisms for the upward motions of dust particles.

Interannual variations in fire weather, fire extent, and synoptic-scale circulation patterns in northern California and Oregon

Treesearch

Valerie Trouet; Alan H. Taylor; Andrew M. Carleton; Carl N. Skinner

2009-01-01

The Mediterranean climate region on the west coast of the United States is characterized by wet winters and dry summers, and by high fire activity. The importance of synoptic-scale circulation patterns (ENSO, PDO, PNA) on fire-climate interactions is evident in contemporary fire data sets and in pre-Euroamerican tree-ring-based fire records. We investigated how...

Overview of the Bushland Evapotranspiration and Agricultural Remote sensing EXperiment 2008 (BEAREX08): A field experiment evaluating methods for quantifying ET at multiple scales

NASA Astrophysics Data System (ADS)

Evett, Steven R.; Kustas, William P.; Gowda, Prasanna H.; Anderson, Martha C.; Prueger, John H.; Howell, Terry A.

2012-12-01

In 2008, scientists from seven federal and state institutions worked together to investigate temporal and spatial variations of evapotranspiration (ET) and surface energy balance in a semi-arid irrigated and dryland agricultural region of the Southern High Plains in the Texas Panhandle. This Bushland Evapotranspiration and Agricultural Remote sensing EXperiment 2008 (BEAREX08) involved determination of micrometeorological fluxes (surface energy balance) in four weighing lysimeter fields (each 4.7 ha) containing irrigated and dryland cotton and in nearby bare soil, wheat stubble and rangeland fields using nine eddy covariance stations, three large aperture scintillometers, and three Bowen ratio systems. In coordination with satellite overpasses, flux and remote sensing aircraft flew transects over the surrounding fields and region encompassing an area contributing fluxes from 10 to 30 km upwind of the USDA-ARS lysimeter site. Tethered balloon soundings were conducted over the irrigated fields to investigate the effect of advection on local boundary layer development. Local ET was measured using four large weighing lysimeters, while field scale estimates were made by soil water balance with a network of neutron probe profile water sites and from the stationary flux systems. Aircraft and satellite imagery were obtained at different spatial and temporal resolutions. Plot-scale experiments dealt with row orientation and crop height effects on spatial and temporal patterns of soil surface temperature, soil water content, soil heat flux, evaporation from soil in the interrow, plant transpiration and canopy and soil radiation fluxes. The BEAREX08 field experiment was unique in its assessment of ET fluxes over a broad range in spatial scales; comparing direct and indirect methods at local scales with remote sensing based methods and models using aircraft and satellite imagery at local to regional scales, and comparing mass balance-based ET ground truth with eddy covariance and remote sensing-based methods. Here we present an overview of the experiment and a summary of preliminary findings described in this special issue of AWR. Our understanding of the role of advection in the measurement and modeling of ET is advanced by these papers integrating measurements and model estimates.

Developing Flexible, Integrated Hydrologic Modeling Systems for Multiscale Analysis in the Midwest and Great Lakes Region

NASA Astrophysics Data System (ADS)

Hamlet, A. F.; Chiu, C. M.; Sharma, A.; Byun, K.; Hanson, Z.

2016-12-01

Physically based hydrologic modeling of surface and groundwater resources that can be flexibly and efficiently applied to support water resources policy/planning/management decisions at a wide range of spatial and temporal scales are greatly needed in the Midwest, where stakeholder access to such tools is currently a fundamental barrier to basic climate change assessment and adaptation efforts, and also the co-production of useful products to support detailed decision making. Based on earlier pilot studies in the Pacific Northwest Region, we are currently assembling a suite of end-to-end tools and resources to support various kinds of water resources planning and management applications across the region. One of the key aspects of these integrated tools is that the user community can access gridded products at any point along the end-to-end chain of models, looking backwards in time about 100 years (1915-2015), and forwards in time about 85 years using CMIP5 climate model projections. The integrated model is composed of historical and projected future meteorological data based on station observations and statistical and dynamically downscaled climate model output respectively. These gridded meteorological data sets serve as forcing data for the macro-scale VIC hydrologic model implemented over the Midwest at 1/16 degree resolution. High-resolution climate model (4km WRF) output provides inputs for the analyses of urban impacts, hydrologic extremes, agricultural impacts, and impacts to the Great Lakes. Groundwater recharge estimated by the surface water model provides input data for fine-scale and macro-scale groundwater models needed for specific applications. To highlight the multi-scale use of the integrated models in support of co-production of scientific information for decision making, we briefly describe three current case studies addressing different spatial scales of analysis: 1) Effects of climate change on the water balance of the Great Lakes, 2) Future hydropower resources in the St. Joseph River basin, 3) Effects of climate change on carbon cycling in small lakes in the Northern Highland Lakes District.

A novel class sensitive hashing technique for large-scale content-based remote sensing image retrieval

NASA Astrophysics Data System (ADS)

Reato, Thomas; Demir, Begüm; Bruzzone, Lorenzo

2017-10-01

This paper presents a novel class sensitive hashing technique in the framework of large-scale content-based remote sensing (RS) image retrieval. The proposed technique aims at representing each image with multi-hash codes, each of which corresponds to a primitive (i.e., land cover class) present in the image. To this end, the proposed method consists of a three-steps algorithm. The first step is devoted to characterize each image by primitive class descriptors. These descriptors are obtained through a supervised approach, which initially extracts the image regions and their descriptors that are then associated with primitives present in the images. This step requires a set of annotated training regions to define primitive classes. A correspondence between the regions of an image and the primitive classes is built based on the probability of each primitive class to be present at each region. All the regions belonging to the specific primitive class with a probability higher than a given threshold are highly representative of that class. Thus, the average value of the descriptors of these regions is used to characterize that primitive. In the second step, the descriptors of primitive classes are transformed into multi-hash codes to represent each image. This is achieved by adapting the kernel-based supervised locality sensitive hashing method to multi-code hashing problems. The first two steps of the proposed technique, unlike the standard hashing methods, allow one to represent each image by a set of primitive class sensitive descriptors and their hash codes. Then, in the last step, the images in the archive that are very similar to a query image are retrieved based on a multi-hash-code-matching scheme. Experimental results obtained on an archive of aerial images confirm the effectiveness of the proposed technique in terms of retrieval accuracy when compared to the standard hashing methods.

Application of Mortar Coupling in Multiscale Modelling of Coupled Flow, Transport, and Biofilm Growth in Porous Media

NASA Astrophysics Data System (ADS)

Laleian, A.; Valocchi, A. J.; Werth, C. J.

2017-12-01

Multiscale models of reactive transport in porous media are capable of capturing complex pore-scale processes while leveraging the efficiency of continuum-scale models. In particular, porosity changes caused by biofilm development yield complex feedbacks between transport and reaction that are difficult to quantify at the continuum scale. Pore-scale models, needed to accurately resolve these dynamics, are often impractical for applications due to their computational cost. To address this challenge, we are developing a multiscale model of biofilm growth in which non-overlapping regions at pore and continuum spatial scales are coupled with a mortar method providing continuity at interfaces. We explore two decompositions of coupled pore-scale and continuum-scale regions to study biofilm growth in a transverse mixing zone. In the first decomposition, all reaction is confined to a pore-scale region extending the transverse mixing zone length. Only solute transport occurs in the surrounding continuum-scale regions. Relative to a fully pore-scale result, we find the multiscale model with this decomposition has a reduced run time and consistent result in terms of biofilm growth and solute utilization. In the second decomposition, reaction occurs in both an up-gradient pore-scale region and a down-gradient continuum-scale region. To quantify clogging, the continuum-scale model implements empirical relations between porosity and continuum-scale parameters, such as permeability and the transverse dispersion coefficient. Solutes are sufficiently mixed at the end of the pore-scale region, such that the initial reaction rate is accurately computed using averaged concentrations in the continuum-scale region. Relative to a fully pore-scale result, we find accuracy of biomass growth in the multiscale model with this decomposition improves as the interface between pore-scale and continuum-scale regions moves downgradient where transverse mixing is more fully developed. Also, this decomposition poses additional challenges with respect to mortar coupling. We explore these challenges and potential solutions. While recent work has demonstrated growing interest in multiscale models, further development is needed for their application to field-scale subsurface contaminant transport and remediation.

Massive mortality of aspen following severe drought along the southern edge of the Canadian boreal forest

PubMed Central

Michaelian, Michael; Hogg, Edward H; Hall, Ronald J; Arsenault, Eric

2011-01-01

Drought-induced, regional-scale dieback of forests has emerged as a global concern that is expected to escalate under model projections of climate change. Since 2000, drought of unusual severity, extent, and duration has affected large areas of western North America, leading to regional-scale dieback of forests in the southwestern US. We report on drought impacts on forests in a region farther north, encompassing the transition between boreal forest and prairie in western Canada. A central question is the significance of drought as an agent of large-scale tree mortality and its potential future impact on carbon cycling in this cold region. We used a combination of plot-based, meteorological, and remote sensing measures to map and quantify aboveground, dead biomass of trembling aspen (Populus tremuloides Michx.) across an 11.5 Mha survey area where drought was exceptionally severe during 2001–2002. Within this area, a satellite-based land cover map showed that aspen-dominated broadleaf forests occupied 2.3 Mha. Aerial surveys revealed extensive patches of severe mortality (>55%) resembling the impacts of fire. Dead aboveground biomass was estimated at 45 Mt, representing 20% of the total aboveground biomass, based on a spatial interpolation of plot-based measurements. Spatial variation in percentage dead biomass showed a moderately strong correlation with drought severity. In the prairie-like, southern half of the study area where the drought was most severe, 35% of aspen biomass was dead, compared with an estimated 7% dead biomass in the absence of drought. Drought led to an estimated 29 Mt increase in dead biomass across the survey area, corresponding to 14 Mt of potential future carbon emissions following decomposition. Many recent, comparable episodes of drought-induced forest dieback have been reported from around the world, which points to an emerging need for multiscale monitoring approaches to quantify drought effects on woody biomass and carbon cycling across large areas.

From BASE-ASIA Toward 7-SEAS: A Satellite-Surface Perspective of Boreal Spring Biomass-Burning Aerosols and Clouds in Southeast Asia

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; Hsu, N. Christina; Lau, William K.-M.; Li, Can; Gabriel, Philip M.; Ji, Qiang; Holben, Brent N.; Welton, E. Judd; Nguyen, Anh X.; Janjai, Serm;

Results from the VALUE perfect predictor experiment: process-based evaluation

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Soares, Pedro; Hertig, Elke; Brands, Swen; Huth, Radan; Cardoso, Rita; Kotlarski, Sven; Casado, Maria; Pongracz, Rita; Bartholy, Judit

2016-04-01

Until recently, the evaluation of downscaled climate model simulations has typically been limited to surface climatologies, including long term means, spatial variability and extremes. But these aspects are often, at least partly, tuned in regional climate models to match observed climate. The tuning issue is of course particularly relevant for bias corrected regional climate models. In general, a good performance of a model for these aspects in present climate does therefore not imply a good performance in simulating climate change. It is now widely accepted that, to increase our condidence in climate change simulations, it is necessary to evaluate how climate models simulate relevant underlying processes. In other words, it is important to assess whether downscaling does the right for the right reason. Therefore, VALUE has carried out a broad process-based evaluation study based on its perfect predictor experiment simulations: the downscaling methods are driven by ERA-Interim data over the period 1979-2008, reference observations are given by a network of 85 meteorological stations covering all European climates. More than 30 methods participated in the evaluation. In order to compare statistical and dynamical methods, only variables provided by both types of approaches could be considered. This limited the analysis to conditioning local surface variables on variables from driving processes that are simulated by ERA-Interim. We considered the following types of processes: at the continental scale, we evaluated the performance of downscaling methods for positive and negative North Atlantic Oscillation, Atlantic ridge and blocking situations. At synoptic scales, we considered Lamb weather types for selected European regions such as Scandinavia, the United Kingdom, the Iberian Pensinsula or the Alps. At regional scales we considered phenomena such as the Mistral, the Bora or the Iberian coastal jet. Such process-based evaluation helps to attribute biases in surface variables to underlying processes and ultimately to improve climate models.

Gas-solid fluidized bed reactors: Scale-up, flow regimes identification and hydrodynamics

NASA Astrophysics Data System (ADS)

Zaid, Faraj Muftah

This research studied the scale-up, flow regimes identification and hydrodynamics of fluidized beds using 6-inch and 18- inch diameter columns and different particles. One of the objectives was to advance the scale-up of gas-solid fluidized bed reactors by developing a new mechanistic methodology for hydrodynamic similarity based on matching the radial or diameter profile of gas phase holdup, since gas dynamics dictate the hydrodynamics of these reactors. This has been successfully achieved. However, the literature reported scale-up methodology based on matching selected dimensionless groups was examined and it was found that it was not easy to match the dimensionless groups and hence, there was some deviation in the hydrodynamics of the studied two different fluidized beds. A new technique based on gamma ray densitometry (GRD) was successfully developed and utilized to on-line monitor the implementation of scale-up, to identify the flow regime, and to measure the radial or diameter profiles of gas and solids holdups. CFD has been demonstrated as a valuable tool to enable the implementation of the newly developed scale-up methodology based on finding the conditions that provide similar or closer radial profile or cross sectional distribution of the gas holdup. As gas velocity increases, solids holdup in the center region of the column decreases in the fully developed region of both 6 inch and 18 inch diameter columns. Solids holdup increased with the increase in the particles size and density. Upflowing particles velocity increased with the gas velocity and became steeper at high superficial gas velocity at all axial heights where the center line velocity became higher than that in the wall region. Smaller particles size and lower density gave larger upflowing particles velocity. Minimum fluidization velocity and transition velocity from bubbly to churn turbulent flow regimes were found to be lower in 18 inch diameter column compared to those obtained in 6 inch diameter column. Also the absolute fluctuation of upflowing particles velocity multiplied by solids holdups vś 3ś as one of the terms for solids mass flux estimation was found to be larger in 18-inch diameter column than that in 6-inch diameter column using same particles size and density.

Earthquake hazard and risk assessment based on Unified Scaling Law for Earthquakes: Greater Caucasus and Crimea

NASA Astrophysics Data System (ADS)

Kossobokov, Vladimir G.; Nekrasova, Anastasia K.

2018-05-01

We continue applying the general concept of seismic risk analysis in a number of seismic regions worldwide by constructing regional seismic hazard maps based on morphostructural analysis, pattern recognition, and the Unified Scaling Law for Earthquakes (USLE), which generalizes the Gutenberg-Richter relationship making use of naturally fractal distribution of earthquake sources of different size in a seismic region. The USLE stands for an empirical relationship log10 N(M, L) = A + B·(5 - M) + C·log10 L, where N(M, L) is the expected annual number of earthquakes of a certain magnitude M within a seismically prone area of linear dimension L. We use parameters A, B, and C of USLE to estimate, first, the expected maximum magnitude in a time interval at seismically prone nodes of the morphostructural scheme of the region under study, then map the corresponding expected ground shaking parameters (e.g., peak ground acceleration, PGA, or macro-seismic intensity). After a rigorous verification against the available seismic evidences in the past (usually, the observed instrumental PGA or the historically reported macro-seismic intensity), such a seismic hazard map is used to generate maps of specific earthquake risks for population, cities, and infrastructures (e.g., those based on census of population, buildings inventory). The methodology of seismic hazard and risk assessment is illustrated by application to the territory of Greater Caucasus and Crimea.

A simple atomic-level hydrophobicity scale reveals protein interfacial structure.

PubMed

Kapcha, Lauren H; Rossky, Peter J

2014-01-23

Many amino acid residue hydrophobicity scales have been created in an effort to better understand and rapidly characterize water-protein interactions based only on protein structure and sequence. There is surprisingly low consistency in the ranking of residue hydrophobicity between scales, and their ability to provide insightful characterization varies substantially across subject proteins. All current scales characterize hydrophobicity based on entire amino acid residue units. We introduce a simple binary but atomic-level hydrophobicity scale that allows for the classification of polar and non-polar moieties within single residues, including backbone atoms. This simple scale is first shown to capture the anticipated hydrophobic character for those whole residues that align in classification among most scales. Examination of a set of protein binding interfaces establishes good agreement between residue-based and atomic-level descriptions of hydrophobicity for five residues, while the remaining residues produce discrepancies. We then show that the atomistic scale properly classifies the hydrophobicity of functionally important regions where residue-based scales fail. To illustrate the utility of the new approach, we show that the atomic-level scale rationalizes the hydration of two hydrophobic pockets and the presence of a void in a third pocket within a single protein and that it appropriately classifies all of the functionally important hydrophilic sites within two otherwise hydrophobic pores. We suggest that an atomic level of detail is, in general, necessary for the reliable depiction of hydrophobicity for all protein surfaces. The present formulation can be implemented simply in a manner no more complex than current residue-based approaches. © 2013.

Improving the sensitivity and specificity of the abbreviated injury scale coding system.

PubMed Central

Kramer, C F; Barancik, J I; Thode, H C

1990-01-01

The Abbreviated Injury Scale with Epidemiologic Modifications (AIS 85-EM) was developed to make it possible to code information about anatomic injury types and locations that, although generally available from medical records, is not codable under the standard Abbreviated Injury Scale, published by the American Association for Automotive Medicine in 1985 (AIS 85). In a population-based sample of 3,223 motor vehicle trauma cases, 68 percent of the patients had one or more injuries that were coded to the AIS 85 body region nonspecific category external. When the same patients' injuries were coded using the AIS 85-EM coding procedure, only 15 percent of the patients had injuries that could not be coded to a specific body region. With AIS 85-EM, the proportion of codable head injury cases increased from 16 percent to 37 percent, thereby improving the potential for identifying cases with head and threshold brain injury. The data suggest that body region coding of all injuries is necessary to draw valid and reliable conclusions about changes in injury patterns and their sequelae. The increased specificity of body region coding improves assessments of the efficacy of injury intervention strategies and countermeasure programs using epidemiologic methodology. PMID:2116633

Reorganization of mental health services: from institutional to community-based models of care.

PubMed

Saraceno, B; Gater, R; Rahman, A; Saeed, K; Eaton, J; Ivbijaro, G; Kidd, M; Dowrick, C; Servili, C; Funk, M K; Underhill, C

2015-09-28

Mental health services in the Eastern Mediterranean Region are predominantly centralized and institutionalized, relying on scarce specialist manpower. This creates a major treatment gap for patients with common and disabling mental disorders and places an unnecessary burden on the individual, their family and society. Six steps for reorganization of mental health services in the Region can be outlined: (1) integrate delivery of interventions for priority mental disorders into primary health care and existing priority programmes; (2) systematically strengthen the capacity of non-specialized health personnel for providing mental health care; (3) scale up community-based services (community outreach teams for defined catchment, supported residential facilities, supported employment and family support); (4) establish mental health services in general hospitals for outpatient and acute inpatient care; (5) progressively reduce the number of long-stay beds in mental hospitals through restricting new admissions; and (6) provide transitional/bridge funding over a period of time to scale up community-based services and downsize mental institutions in parallel.

On the use of Schwarz-Christoffel conformal mappings to the grid generation for global ocean models

NASA Astrophysics Data System (ADS)

Xu, S.; Wang, B.; Liu, J.

2015-02-01

In this article we propose two conformal mapping based grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithms are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the basic grid design problem of pole relocation, these new algorithms also address more advanced issues such as smoothed scaling factor, or the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling where complex land-ocean distribution is present.

Line fitting based feature extraction for object recognition

NASA Astrophysics Data System (ADS)

Li, Bing

2014-06-01

Image feature extraction plays a significant role in image based pattern applications. In this paper, we propose a new approach to generate hierarchical features. This new approach applies line fitting to adaptively divide regions based upon the amount of information and creates line fitting features for each subsequent region. It overcomes the feature wasting drawback of the wavelet based approach and demonstrates high performance in real applications. For gray scale images, we propose a diffusion equation approach to map information-rich pixels (pixels near edges and ridge pixels) into high values, and pixels in homogeneous regions into small values near zero that form energy map images. After the energy map images are generated, we propose a line fitting approach to divide regions recursively and create features for each region simultaneously. This new feature extraction approach is similar to wavelet based hierarchical feature extraction in which high layer features represent global characteristics and low layer features represent local characteristics. However, the new approach uses line fitting to adaptively focus on information-rich regions so that we avoid the feature waste problems of the wavelet approach in homogeneous regions. Finally, the experiments for handwriting word recognition show that the new method provides higher performance than the regular handwriting word recognition approach.

Analyzing energy-water exchange dynamics in the Thar desert

NASA Astrophysics Data System (ADS)

Raja, P.; Singh, Nilendu; Srinivas, C. V.; Singhal, Mohit; Chauhan, Pankaj; Singh, Maharaj; Sinha, N. K.

2017-07-01

Regions of strong land-atmosphere coupling will be more susceptible to the hydrological impacts in the intensifying hydrological cycle. In this study, micrometeorological experiments were performed to examine the land-atmosphere coupling strength over a heat low region (Thar desert, NW India), known to influence the Indian summer monsoon (ISM). Within the vortex of Thar desert heat low, energy-water exchange and coupling behavior were studied for 4 consecutive years (2011-2014) based on sub-hourly measurements of radiative-convective flux, state parameters and sub-surface thermal profiles using lead-lag analysis between various E-W balance components. Results indicated a strong (0.11-0.35) but variable monsoon season (July-September) land-atmosphere coupling events. Coupling strength declined with time, becomes negative beyond 10-day lag. Evapotranspiration (LE) influences rainfall at the monthly time-scale (20-40 days). Highly correlated monthly rainfall and LE anomalies (r = 0.55, P < 0.001) suggested a large precipitation memory linked to the local land surface state. Sensible heating (SH) during March and April are more strongly (r = 0.6-0.7) correlated to ISM rainfall than heating during May or June (r = 0.16-0.36). Analyses show strong and weak couplings among net radiation (Rn)-vapour pressure deficit (VPD), LE-VPD and Rn-LE switching between energy-limited to water-limited conditions. Consistently, +ve and -ve residual energy [(dE) = (Rn - G) - (SH + LE)] were associated with regional wet and dry spells respectively with a lead of 10-40 days. Dew deposition (18.8-37.9 mm) was found an important component in the annual surface water balance. Strong association of variation of LE and rainfall was found during monsoon at local-scale and with regional-scale LE (MERRA 2D) but with a lag which was more prominent at local-scale than at regional-scale. Higher pre-monsoon LE at local-scale as compared to low and monotonous variation in regional-scale LE led to hypothesize that excess energy and water vapour brought through advection caused by pre-monsoon rainfall might have been recycled through rainfall to compensate for early part of monsoon rainfall at local-scale. However, long-term measurements and isotope analysis would be able to strengthen this hypothesis. This study would fill the key gaps in the global flux studies and improve understanding on local E-W exchange pathways, responses and feedbacks.

A New Freshwater Naked Lobose Amoeba Korotnevella venosa n. sp. (Amoebozoa, Discosea).

PubMed

Udalov, Ilya A; Zlatogursky, Vasily V; Smirnov, Alexey V

2016-11-01

A new freshwater species of naked lobose amoebae Korotnevella venosa n. sp. isolated from freshwater pond in St. Petersburg, Russia was studied with light and transmission electron microscopy. Basket scales of this species have six vertical columns supporting perforated rim. The latter has tongue-like broadening with membranous region. Vertical columns bifurcate at both ends so that neighboring columns are connected by their bifurcations forming combined structure. Basket scales of K. venosa are similar to those of Korotnevella hemistylolepis in having six full-length vertical columns and perforated rim. At the same time, they are different in having tongue-like broadening of perforated rim with membranous region and absence of six half-length columns and an intermediate crosspiece. Phylogenetic trees based on 18S rDNA gene placed K. venosa either at the base of the whole Korotnevella clade, next to K. hemistylolepis, or as a sister to the clade comprising Korotnevella species with latticework basket in large scales. © 2016 The Author(s) Journal of Eukaryotic Microbiology © 2016 International Society of Protistologists.

Regional trends in short-duration precipitation extremes: a flexible multivariate monotone quantile regression approach

NASA Astrophysics Data System (ADS)

Cannon, Alex

2017-04-01

Estimating historical trends in short-duration rainfall extremes at regional and local scales is challenging due to low signal-to-noise ratios and the limited availability of homogenized observational data. In addition to being of scientific interest, trends in rainfall extremes are of practical importance, as their presence calls into question the stationarity assumptions that underpin traditional engineering and infrastructure design practice. Even with these fundamental challenges, increasingly complex questions are being asked about time series of extremes. For instance, users may not only want to know whether or not rainfall extremes have changed over time, they may also want information on the modulation of trends by large-scale climate modes or on the nonstationarity of trends (e.g., identifying hiatus periods or periods of accelerating positive trends). Efforts have thus been devoted to the development and application of more robust and powerful statistical estimators for regional and local scale trends. While a standard nonparametric method like the regional Mann-Kendall test, which tests for the presence of monotonic trends (i.e., strictly non-decreasing or non-increasing changes), makes fewer assumptions than parametric methods and pools information from stations within a region, it is not designed to visualize detected trends, include information from covariates, or answer questions about the rate of change in trends. As a remedy, monotone quantile regression (MQR) has been developed as a nonparametric alternative that can be used to estimate a common monotonic trend in extremes at multiple stations. Quantile regression makes efficient use of data by directly estimating conditional quantiles based on information from all rainfall data in a region, i.e., without having to precompute the sample quantiles. The MQR method is also flexible and can be used to visualize and analyze the nonlinearity of the detected trend. However, it is fundamentally a univariate technique, and cannot incorporate information from additional covariates, for example ENSO state or physiographic controls on extreme rainfall within a region. Here, the univariate MQR model is extended to allow the use of multiple covariates. Multivariate monotone quantile regression (MMQR) is based on a single hidden-layer feedforward network with the quantile regression error function and partial monotonicity constraints. The MMQR model is demonstrated via Monte Carlo simulations and the estimation and visualization of regional trends in moderate rainfall extremes based on homogenized sub-daily precipitation data at stations in Canada.

A joint prevention and control mechanism for air pollution in the Beijing-Tianjin-Hebei region in china based on long-term and massive data mining of pollutant concentration

NASA Astrophysics Data System (ADS)

Wang, Hongbo; Zhao, Laijun

2018-02-01

China's Beijing-Tianjin-Hebei (BTH) region suffers from the country's worst air pollution. The problem has caused widespread concern both at home and abroad. Based on long-term and massive data mining of PM2.5 and PM10 concentration, we found that these pollutants showed similar variations in four seasons, but the most severe pollution was in winter. Through cluster analysis of the winter daily average concentration (DAC) of the two pollutants, we defined regions with similar variations in pollutant concentrations in winter. For the most polluted cities in BTH, the relationship between correlation coefficients for winter DAC and the distance between cities revealed that PM2.5 has regional, large-scale characteristics, with concentrated outbreaks, whereas PM10 has local, small-scale characteristics, with outbreaks at multiple locations. By selecting the key cities with the strongest linear relationship between the pollutant's DAC of each city and the daily individual air quality index values of the BTH region and through cluster analysis on the correlations between the pollutant DACs of the key cities, we defined regional divisions suitable for Joint Prevention and Control of Atmospheric Pollution (JPCAP) program to control PM2.5 and PM10. Comprehensively considering the degree of influence of regional atmospheric pollution control (RAPC) on air quality in BTH, as well as the elasticity and urgency of RAPC, we defined the control grades of the JPCAP regions. We found both the regions and corresponding control grades were consistent for PM2.5 and PM10. The thinking and methods of atmospheric pollution control we proposed will have broad significance for implementation of RAPC in other regions around the world.

Scaling up the diversity-resilience relationship with trait databases and remote sensing data: the recovery of productivity after wildfire.

PubMed

Spasojevic, Marko J; Bahlai, Christie A; Bradley, Bethany A; Butterfield, Bradley J; Tuanmu, Mao-Ning; Sistla, Seeta; Wiederholt, Ruscena; Suding, Katharine N

2016-04-01

Understanding the mechanisms underlying ecosystem resilience - why some systems have an irreversible response to disturbances while others recover - is critical for conserving biodiversity and ecosystem function in the face of global change. Despite the widespread acceptance of a positive relationship between biodiversity and resilience, empirical evidence for this relationship remains fairly limited in scope and localized in scale. Assessing resilience at the large landscape and regional scales most relevant to land management and conservation practices has been limited by the ability to measure both diversity and resilience over large spatial scales. Here, we combined tools used in large-scale studies of biodiversity (remote sensing and trait databases) with theoretical advances developed from small-scale experiments to ask whether the functional diversity within a range of woodland and forest ecosystems influences the recovery of productivity after wildfires across the four-corner region of the United States. We additionally asked how environmental variation (topography, macroclimate) across this geographic region influences such resilience, either directly or indirectly via changes in functional diversity. Using path analysis, we found that functional diversity in regeneration traits (fire tolerance, fire resistance, resprout ability) was a stronger predictor of the recovery of productivity after wildfire than the functional diversity of seed mass or species richness. Moreover, slope, elevation, and aspect either directly or indirectly influenced the recovery of productivity, likely via their effect on microclimate, while macroclimate had no direct or indirect effects. Our study provides some of the first direct empirical evidence for functional diversity increasing resilience at large spatial scales. Our approach highlights the power of combining theory based on local-scale studies with tools used in studies at large spatial scales and trait databases to understand pressing environmental issues. © 2015 John Wiley & Sons Ltd.

Placing Local Aggregations in a Larger-Scale Context: Hierarchical Modeling of Black-Footed Albatross Dispersion.

PubMed

Michael, P E; Jahncke, J; Hyrenbach, K D

2016-01-01

At-sea surveys facilitate the study of the distribution and abundance of marine birds along standardized transects, in relation to changes in the local environmental conditions and large-scale oceanographic forcing. We analyzed the form and the intensity of black-footed albatross (Phoebastria nigripes: BFAL) spatial dispersion off central California, using five years (2004-2008) of vessel-based surveys of seven replicated survey lines. We related BFAL patchiness to local, regional and basin-wide oceanographic variability using two complementary approaches: a hypothesis-based model and an exploratory analysis. The former tested the strength and sign of hypothesized BFAL responses to environmental variability, within a hierarchical atmosphere-ocean context. The latter explored BFAL cross-correlations with atmospheric / oceanographic variables. While albatross dispersion was not significantly explained by the hierarchical model, the exploratory analysis revealed that aggregations were influenced by static (latitude, depth) and dynamic (wind speed, upwelling) environmental variables. Moreover, the largest BFAL patches occurred along the survey lines with the highest densities, and in association with shallow banks. In turn, the highest BFAL densities occurred during periods of negative Pacific Decadal Oscillation index values and low atmospheric pressure. The exploratory analyses suggest that BFAL dispersion is influenced by basin-wide, regional-scale and local environmental variability. Furthermore, the hypothesis-based model highlights that BFAL do not respond to oceanographic variability in a hierarchical fashion. Instead, their distributions shift more strongly in response to large-scale ocean-atmosphere forcing. Thus, interpreting local changes in BFAL abundance and dispersion requires considering diverse environmental forcing operating at multiple scales.

Synthesis of regional crust and upper-mantle structure from seismic and gravity data

NASA Technical Reports Server (NTRS)

Alexander, S. S.; Lavin, P. M.

1979-01-01

Available seismic and ground based gravity data are combined to infer the three dimensional crust and upper mantle structure in selected regions. This synthesis and interpretation proceeds from large-scale average models suitable for early comparison with high-altitude satellite potential field data to more detailed delineation of structural boundaries and other variations that may be significant in natural resource assessment. Seismic and ground based gravity data are the primary focal point, but other relevant information (e.g. magnetic field, heat flow, Landsat imagery, geodetic leveling, and natural resources maps) is used to constrain the structure inferred and to assist in defining structural domains and boundaries. The seismic data consists of regional refraction lines, limited reflection coverage, surface wave dispersion, teleseismic P and S wave delay times, anelastic absorption, and regional seismicity patterns. The gravity data base consists of available point gravity determinations for the areas considered.

East African wetland-catchment data base for sustainable wetland management

NASA Astrophysics Data System (ADS)

Leemhuis, Constanze; Amler, Esther; Diekkrüger, Bernd; Gabiri, Geofrey; Näschen, Kristian

2016-10-01

Wetlands cover an area of approx. 18 Mio ha in the East African countries of Kenya, Rwanda, Uganda and Tanzania, with still a relative small share being used for food production. Current upland agricultural use intensification in these countries due to demographic growth, climate change and globalization effects are leading to an over-exploitation of the resource base, followed by an intensification of agricultural wetland use. We aim on translating, transferring and upscaling knowledge on experimental test-site wetland properties, small-scale hydrological processes, and water related ecosystem services under different types of management from local to national scale. This information gained at the experimental wetland/catchment scale will be embedded as reference data within an East African wetland-catchment data base including catchment physical properties and a regional wetland inventory serving as a base for policy advice and the development of sustainable wetland management strategies.

ATMOSPHERIC AMMONIA EMISSIONS FROM THE LIVESTOCK SECTOR: DEVELOPMENT AND EVALUATION OF A PROCESS-BASED MODELING APPROACH

EPA Science Inventory

We propose multi-faceted research to enhance our understanding of NH3 emissions from livestock feeding operations. A process-based emissions modeling approach will be used, and we will investigate ammonia emissions from the scale of the individual farm out to impacts on region...

A thermal-based remote sensing modelling system for estimating crop water use and stress from field to regional scales

USDA-ARS?s Scientific Manuscript database

Thermal-infrared remote sensing of land surface temperature provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition. A thermal-based scheme, called the Two-Source Energy Balance (TSEB) model, solves for the soil/substrate and canopy temp...

Dry Particulate Nitrate Deposition in China.

PubMed

Liu, Lei; Zhang, Xiuying; Zhang, Yan; Xu, Wen; Liu, Xuejun; Zhang, Xiaomin; Feng, Junlan; Chen, Xinrui; Zhang, Yuehan; Lu, Xuehe; Wang, Shanqian; Zhang, Wuting; Zhao, Limin

2017-05-16

A limited number of ground measurements of dry particulate nitrate deposition (NO 3 - ) makes it difficult and challenging to fully know the status of the spatial and temporal variations of dry NO 3 - depositions over China. This study tries to expand the ground measurements of NO 3 - concentrations at monitoring sites to a national scale, based on the Ozone Monitoring Instrument (OMI) NO 2 columns, NO 2 profiles from an atmospheric chemistry transport model (Model for Ozone and Related chemical Tracers, version 4, MOZART-4) and monitor-based sources, and then estimates the NO 3 - depositions on a regional scale based on an inferred model. The ground NO 2 concentrations were first derived from NO 2 columns and the NO 2 profiles, and then the ground NO 3 - concentrations were derived from the ground NO 2 concentrations and the relationship between NO 2 and NO 3 - based on Chinese Nationwide Nitrogen Deposition Monitoring Network (NNDMN). This estimated dry NO 3 - depositions over China will be helpful in determining the magnitude and pollution status in regions without ground measurements, supporting the construction plan of environmental monitoring in future.

The roles of precipitation regimes on juniper forest encroachment on grasslands in Oklahoma

NASA Astrophysics Data System (ADS)

Wang, J.; Xiao, X.; Qin, Y.

2017-12-01

Woody plant encroachment into grasslands has been dominantly explained by fire suppression, grazing and CO2 concentrations in the atmosphere. As different root depths of grasses and trees in soils, increased precipitation intensity was expected to facilitate the woody plant abundance, which was demonstrated by the field precipitation test in a sub-tropical savanna ecosystem. However, it is lacking to compressively examine the roles of precipitation regimes on woody plant encroachment at regional scales based on long-term observation data. This study examined the relationships between changes of precipitation regimes (amounts, frequency and intensity) and dynamics of juniper forest coverage using site-based rainfall data and remote sensing-based juniper forest maps in 1994-2010 over Oklahoma State. Our results showed that precipitation amount and intensity played larger roles than frequency on the juniper forest encroachment into the grassland in Oklahoma, and increased precipitation amount and intensity could facilitate the juniper woody encroachment. This practice based on observation data at the regional scale could be used to support precipitation experiments and model simulations and predicting the juniper forest encroachment.

Development of a pulsed 9.5 micron lidar for regional scale O3 measurement

NASA Technical Reports Server (NTRS)

Stewart, R. W.

1980-01-01

A pulsed infrared lidar system designed for application to the remote sensing of atmospheric trace gases from an airborne platform is described. The system is also capable of measuring the infrared backscatter characteristics of the ocean surface, terrain, cloud, and aerosol targets. The lidar employed is based on dual wavelength pulse energy measurements in the 9-11 micrometer wavelength region.

Disturbance, tree mortality, and implications for contemporary regional forest change in the Pacific Northwest

Treesearch

Matthew J. Reilly; Thomas A. Spies

2016-01-01

Tree mortality is an important demographic process and primary driver of forest dynamics, yet there are relatively few plot-based studies that explicitly quantify mortality and compare the relative contribution of endogenous and exogenous disturbances at regional scales. We used repeated observations on 289,390 trees in 3673 1 ha plots on U.S. Forest Service lands in...

Development of Activity-based Cost Functions for Cellulase, Invertase, and Other Enzymes

NASA Astrophysics Data System (ADS)

Stowers, Chris C.; Ferguson, Elizabeth M.; Tanner, Robert D.

As enzyme chemistry plays an increasingly important role in the chemical industry, cost analysis of these enzymes becomes a necessity. In this paper, we examine the aspects that affect the cost of enzymes based upon enzyme activity. The basis for this study stems from a previously developed objective function that quantifies the tradeoffs in enzyme purification via the foam fractionation process (Cherry et al., Braz J Chem Eng 17:233-238, 2000). A generalized cost function is developed from our results that could be used to aid in both industrial and lab scale chemical processing. The generalized cost function shows several nonobvious results that could lead to significant savings. Additionally, the parameters involved in the operation and scaling up of enzyme processing could be optimized to minimize costs. We show that there are typically three regimes in the enzyme cost analysis function: the low activity prelinear region, the moderate activity linear region, and high activity power-law region. The overall form of the cost analysis function appears to robustly fit the power law form.

Can We Use Regression Modeling to Quantify Mean Annual Streamflow at a Global-Scale?

NASA Astrophysics Data System (ADS)

Barbarossa, V.; Huijbregts, M. A. J.; Hendriks, J. A.; Beusen, A.; Clavreul, J.; King, H.; Schipper, A.

2016-12-01

Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for a number of applications, including assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict MAF based on climate and catchment characteristics. Yet, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. In this study, we developed a global-scale regression model for MAF using observations of discharge and catchment characteristics from 1,885 catchments worldwide, ranging from 2 to 106 km2 in size. In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB [van Beek et al., 2011] by comparing results from both models to independent measurements. We obtained a regression model explaining 89% of the variance in MAF based on catchment area, mean annual precipitation and air temperature, average slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error values were lower (0.29 - 0.38 compared to 0.49 - 0.57) and the modified index of agreement was higher (0.80 - 0.83 compared to 0.72 - 0.75). Our regression model can be applied globally at any point of the river network, provided that the input parameters are within the range of values employed in the calibration of the model. The performance is reduced for water scarce regions and further research should focus on improving such an aspect for regression-based global hydrological models.

Bush Encroachment Mapping for Africa - Multi-Scale Analysis with Remote Sensing and GIS

NASA Astrophysics Data System (ADS)

Graw, V. A. M.; Oldenburg, C.; Dubovyk, O.

2015-12-01

Bush encroachment describes a global problem which is especially facing the savanna ecosystem in Africa. Livestock is directly affected by decreasing grasslands and inedible invasive species which defines the process of bush encroachment. For many small scale farmers in developing countries livestock represents a type of insurance in times of crop failure or drought. Among that bush encroachment is also a problem for crop production. Studies on the mapping of bush encroachment so far focus on small scales using high-resolution data and rarely provide information beyond the national level. Therefore a process chain was developed using a multi-scale approach to detect bush encroachment for whole Africa. The bush encroachment map is calibrated with ground truth data provided by experts in Southern, Eastern and Western Africa. By up-scaling location specific information on different levels of remote sensing imagery - 30m with Landsat images and 250m with MODIS data - a map is created showing potential and actual areas of bush encroachment on the African continent and thereby provides an innovative approach to map bush encroachment on the regional scale. A classification approach links location data based on GPS information from experts to the respective pixel in the remote sensing imagery. Supervised classification is used while actual bush encroachment information represents the training samples for the up-scaling. The classification technique is based on Random Forests and regression trees, a machine learning classification approach. Working on multiple scales and with the help of field data an innovative approach can be presented showing areas affected by bush encroachment on the African continent. This information can help to prevent further grassland decrease and identify those regions where land management strategies are of high importance to sustain livestock keeping and thereby also secure livelihoods in rural areas.

Sea Surface Temperature Influence on Terrestrial Gross Primary Production along the Southern California Current.

PubMed

Reimer, Janet J; Vargas, Rodrigo; Rivas, David; Gaxiola-Castro, Gilberto; Hernandez-Ayon, J Martin; Lara-Lara, Ruben

2015-01-01

Some land and ocean processes are related through connections (and synoptic-scale teleconnections) to the atmosphere. Synoptic-scale atmospheric (El Niño/Southern Oscillation [ENSO], Pacific Decadal Oscillation [PDO], and North Atlantic Oscillation [NAO]) decadal cycles are known to influence the global terrestrial carbon cycle. Potentially, smaller scale land-ocean connections influenced by coastal upwelling (changes in sea surface temperature) may be important for local-to-regional water-limited ecosystems where plants may benefit from air moisture transported from the ocean to terrestrial ecosystems. Here we use satellite-derived observations to test potential connections between changes in sea surface temperature (SST) in regions with strong coastal upwelling and terrestrial gross primary production (GPP) across the Baja California Peninsula. This region is characterized by an arid/semiarid climate along the southern California Current. We found that SST was correlated with the fraction of photosynthetic active radiation (fPAR; as a proxy for GPP) with lags ranging from 0 to 5 months. In contrast ENSO was not as strongly related with fPAR as SST in these coastal ecosystems. Our results show the importance of local-scale changes in SST during upwelling events, to explain the variability in GPP in coastal, water-limited ecosystems. The response of GPP to SST was spatially-dependent: colder SST in the northern areas increased GPP (likely by influencing fog formation), while warmer SST at the southern areas was associated to higher GPP (as SST is in phase with precipitation patterns). Interannual trends in fPAR are also spatially variable along the Baja California Peninsula with increasing secular trends in subtropical regions, decreasing trends in the most arid region, and no trend in the semi-arid regions. These findings suggest that studies and ecosystem process based models should consider the lateral influence of local-scale ocean processes that could influence coastal ecosystem productivity.

Sea Surface Temperature Influence on Terrestrial Gross Primary Production along the Southern California Current

PubMed Central

Reimer, Janet J.; Vargas, Rodrigo; Rivas, David; Gaxiola-Castro, Gilberto; Hernandez-Ayon, J. Martin; Lara-Lara, Ruben

2015-01-01

Some land and ocean processes are related through connections (and synoptic-scale teleconnections) to the atmosphere. Synoptic-scale atmospheric (El Niño/Southern Oscillation [ENSO], Pacific Decadal Oscillation [PDO], and North Atlantic Oscillation [NAO]) decadal cycles are known to influence the global terrestrial carbon cycle. Potentially, smaller scale land-ocean connections influenced by coastal upwelling (changes in sea surface temperature) may be important for local-to-regional water-limited ecosystems where plants may benefit from air moisture transported from the ocean to terrestrial ecosystems. Here we use satellite-derived observations to test potential connections between changes in sea surface temperature (SST) in regions with strong coastal upwelling and terrestrial gross primary production (GPP) across the Baja California Peninsula. This region is characterized by an arid/semiarid climate along the southern California Current. We found that SST was correlated with the fraction of photosynthetic active radiation (fPAR; as a proxy for GPP) with lags ranging from 0 to 5 months. In contrast ENSO was not as strongly related with fPAR as SST in these coastal ecosystems. Our results show the importance of local-scale changes in SST during upwelling events, to explain the variability in GPP in coastal, water-limited ecosystems. The response of GPP to SST was spatially-dependent: colder SST in the northern areas increased GPP (likely by influencing fog formation), while warmer SST at the southern areas was associated to higher GPP (as SST is in phase with precipitation patterns). Interannual trends in fPAR are also spatially variable along the Baja California Peninsula with increasing secular trends in subtropical regions, decreasing trends in the most arid region, and no trend in the semi-arid regions. These findings suggest that studies and ecosystem process based models should consider the lateral influence of local-scale ocean processes that could influence coastal ecosystem productivity. PMID:25923109

Downscaling Soil Moisture in the Southern Great Plains Through a Calibrated Multifractal Model for Land Surface Modeling Applications

NASA Technical Reports Server (NTRS)

Mascaro, Giuseppe; Vivoni, Enrique R.; Deidda, Roberto

2010-01-01

Accounting for small-scale spatial heterogeneity of soil moisture (theta) is required to enhance the predictive skill of land surface models. In this paper, we present the results of the development, calibration, and performance evaluation of a downscaling model based on multifractal theory using aircraft!based (800 m) theta estimates collected during the southern Great Plains experiment in 1997 (SGP97).We first demonstrate the presence of scale invariance and multifractality in theta fields of nine square domains of size 25.6 x 25.6 sq km, approximately a satellite footprint. Then, we estimate the downscaling model parameters and evaluate the model performance using a set of different calibration approaches. Results reveal that small-scale theta distributions are adequately reproduced across the entire region when coarse predictors include a dynamic component (i.e., the spatial mean soil moisture ) and a stationary contribution accounting for static features (i.e., topography, soil texture, vegetation). For wet conditions, we found similar multifractal properties of soil moisture across all domains, which we ascribe to the signature of rainfall spatial variability. For drier states, the theta fields in the northern domains are more intermittent than in southern domains, likely because of differences in the distribution of vegetation coverage. Through our analyses, we propose a regional downscaling relation for coarse, satellite-based soil moisture estimates, based on ancillary information (static and dynamic landscape features), which can be used in the study area to characterize statistical properties of small-scale theta distribution required by land surface models and data assimilation systems.

Canopy BRF simulation of forest with different crown shape and height in larger scale based on Radiosity method

NASA Astrophysics Data System (ADS)

Song, Jinling; Qu, Yonghua; Wang, Jindi; Wan, Huawei; Liu, Xiaoqing

2007-06-01

Radiosity method is based on the computer simulation of 3D real structures of vegetations, such as leaves, branches and stems, which are composed by many facets. Using this method we can simulate the canopy reflectance and its bidirectional distribution of the vegetation canopy in visible and NIR regions. But with vegetations are more complex, more facets to compose them, so large memory and lots of time to calculate view factors are required, which are the choke points of using Radiosity method to calculate canopy BRF of lager scale vegetation scenes. We derived a new method to solve the problem, and the main idea is to abstract vegetation crown shapes and to simplify their structures, which can lessen the number of facets. The facets are given optical properties according to the reflectance, transmission and absorption of the real structure canopy. Based on the above work, we can simulate the canopy BRF of the mix scenes with different species vegetation in the large scale. In this study, taking broadleaf trees as an example, based on their structure characteristics, we abstracted their crowns as ellipsoid shells, and simulated the canopy BRF in visible and NIR regions of the large scale scene with different crown shape and different height ellipsoids. Form this study, we can conclude: LAI, LAD the probability gap, the sunlit and shaded surfaces are more important parameter to simulate the simplified vegetation canopy BRF. And the Radiosity method can apply us canopy BRF data in any conditions for our research.

Generating High Resolution Climate Scenarios Through Regional Climate Modelling Over Southern Africa

NASA Astrophysics Data System (ADS)

Ndhlovu, G. Z.; Woyessa, Y. E.; Vijayaraghavan, S.

2017-12-01

limate change has impacted the global environment and the Continent of Africa, especially Southern Africa, regarded as one of the most vulnerable regions in Africa, has not been spared from these impacts. Global Climate Models (GCMs) with coarse horizontal resolutions of 150-300 km do not provide sufficient details at the local basin scale due to mismatch between the size of river basins and the grid cell of the GCM. This makes it difficult to apply the outputs of GCMs directly to impact studies such as hydrological modelling. This necessitates the use of regional climate modelling at high resolutions that provide detailed information at regional and local scales to study both climate change and its impacts. To this end, an experiment was set up and conducted with PRECIS, a regional climate model, to generate climate scenarios at a high resolution of 25km for the local region in Zambezi River basin of Southern Africa. The major input data used included lateral and surface boundary conditions based on the GCMs. The data is processed, analysed and compared with CORDEX climate change project data generated for Africa. This paper, highlights the major differences of the climate scenarios generated by PRECIS Model and CORDEX Project for Africa and further gives recommendations for further research on generation of climate scenarios. The climatic variables such as precipitation and temperatures have been analysed for flood and droughts in the region. The paper also describes the setting up and running of an experiment using a high-resolution PRECIS model. In addition, a description has been made in running the model and generating the output variables on a sub basin scale. Regional climate modelling which provides information on climate change impact may lead to enhanced understanding of adaptive water resources management. Understanding the regional climate modelling results on sub basin scale is the first step in analysing complex hydrological processes and a basis for designing of adaptation and mitigation strategies in the region. Key words: Climate change, regional climate modelling, hydrological processes, extremes, scenarios [1] Corresponding author: Email:gndhlovu@cut.ac.za Tel:+27 (0) 51 507 3072

PARSEC-SCALE SHOCKS IN THE KILOPARSEC-SCALE JET OF CENTAURUS A

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

Tingay, S. J.; Lenc, E.

2009-09-15

High angular resolution very long baseline interferometry (VLBI) observations of Centaurus A have been undertaken that allow access to a wide field of view, encompassing both the well-studied parsec-scale jet and the inner part of the kiloparsec-scale jet. The VLBI observations have detected compact regions of synchrotron emission in the kiloparsec-scale jet that coincide with three stationary features identified from previous VLA monitoring observations. Each of these stationary features is associated with strong localized X-ray emission. The VLBI results strengthen arguments made by previous authors suggesting that the stationary features may be the result of stellar objects or gas cloudsmore » traversing the jet flow, intercepting the jet and causing strong shocks. The VLBI data show that the most strongly shocked regions in these features are resolved but have extents no larger than a few pc, reducing the required mass of the typical intercepting object by a factor of {approx}10 relative to previous estimates, making explanations based on high mass-loss stars or low-density gas clouds more plausible.« less

Similarity spectra analysis of high-performance jet aircraft noise.

PubMed

Neilsen, Tracianne B; Gee, Kent L; Wall, Alan T; James, Michael M

2013-04-01

Noise measured in the vicinity of an F-22A Raptor has been compared to similarity spectra found previously to represent mixing noise from large-scale and fine-scale turbulent structures in laboratory-scale jet plumes. Comparisons have been made for three engine conditions using ground-based sideline microphones, which covered a large angular aperture. Even though the nozzle geometry is complex and the jet is nonideally expanded, the similarity spectra do agree with large portions of the measured spectra. Toward the sideline, the fine-scale similarity spectrum is used, while the large-scale similarity spectrum provides a good fit to the area of maximum radiation. Combinations of the two similarity spectra are shown to match the data in between those regions. Surprisingly, a combination of the two is also shown to match the data at the farthest aft angle. However, at high frequencies the degree of congruity between the similarity and the measured spectra changes with engine condition and angle. At the higher engine conditions, there is a systematically shallower measured high-frequency slope, with the largest discrepancy occurring in the regions of maximum radiation.

Micron-scale coherence in interphase chromatin dynamics

PubMed Central

Zidovska, Alexandra; Weitz, David A.; Mitchison, Timothy J.

2013-01-01

Chromatin structure and dynamics control all aspects of DNA biology yet are poorly understood, especially at large length scales. We developed an approach, displacement correlation spectroscopy based on time-resolved image correlation analysis, to map chromatin dynamics simultaneously across the whole nucleus in cultured human cells. This method revealed that chromatin movement was coherent across large regions (4–5 µm) for several seconds. Regions of coherent motion extended beyond the boundaries of single-chromosome territories, suggesting elastic coupling of motion over length scales much larger than those of genes. These large-scale, coupled motions were ATP dependent and unidirectional for several seconds, perhaps accounting for ATP-dependent directed movement of single genes. Perturbation of major nuclear ATPases such as DNA polymerase, RNA polymerase II, and topoisomerase II eliminated micron-scale coherence, while causing rapid, local movement to increase; i.e., local motions accelerated but became uncoupled from their neighbors. We observe similar trends in chromatin dynamics upon inducing a direct DNA damage; thus we hypothesize that this may be due to DNA damage responses that physically relax chromatin and block long-distance communication of forces. PMID:24019504

The vertical hydraulic conductivity of an aquitard at two spatial scales

USGS Publications Warehouse

Hart, D.J.; Bradbury, K.R.; Feinstein, D.T.

2006-01-01

Aquitards protect underlying aquifers from contaminants and limit recharge to those aquifers. Understanding the mechanisms and quantity of ground water flow across aquitards to underlying aquifers is essential for ground water planning and assessment. We present results of laboratory testing for shale hydraulic conductivities, a methodology for determining the vertical hydraulic conductivity (Kv) of aquitards at regional scales and demonstrate the importance of discrete flow pathways across aquitards. A regional shale aquitard in southeastern Wisconsin, the Maquoketa Formation, was studied to define the role that an aquitard plays in a regional ground water flow system. Calibration of a regional ground water flow model for southeastern Wisconsin using both predevelopment steady-state and transient targets suggested that the regional Kv of the Maquoketa Formation is 1.8 ?? 10 -11 m/s. The core-scale measurements of the Kv of the Maquoketa Formation range from 1.8 ?? 10-14 to 4.1 ?? 10-12 m/s. Flow through some additional pathways in the shale, potential fractures or open boreholes, can explain the apparent increase of the regional-scale Kv. Based on well logs, erosional windows or high-conductivity zones seem unlikely pathways. Fractures cutting through the entire thickness of the shale spaced 5 km apart with an aperture of 50 microns could provide enough flow across the aquitard to match that provided by an equivalent bulk Kv of 1.8 ?? 10-11 m/s. In a similar fashion, only 50 wells of 0.1 m radius open to aquifers above and below the shale and evenly spaced 10 km apart across southeastern Wisconsin can match the model Kv. Copyright ?? 2005 National Ground Water Association.

Effects of trade openness and market scale on different regions

NASA Astrophysics Data System (ADS)

Tian, Renqu; Yang, Zisheng

2017-04-01

This paper revisits the relationship between growth, trade openness and market scale. Empirical studies have provided that area develops lopsided problem in China is increasingly serious, while large trade openness and market scale bring about more economic growth. We use a number of data set from province-level’s gross domestic product and socio-economic, as well as statistical methods panel ordinary least squares and instrumental variables estimation techniques to explore the effects of trade openness and regional market scale on the three major economic regions. The results indicate: Firstly, the impact of market scale and trade openness on economic growth is found to be positive. Secondly, the overall regional disparity is owing to the trade openness, market scale and macroeconomic policies. Thirdly, midland and western region should take advantage of regional geographical location and resource to expand exports and narrow the regional difference.

Analysis techniques for background rejection at the Majorana Demonstrator

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

Cuestra, Clara; Rielage, Keith Robert; Elliott, Steven Ray

2015-06-11

The MAJORANA Collaboration is constructing the MAJORANA DEMONSTRATOR, an ultra-low background, 40-kg modular HPGe detector array to search for neutrinoless double beta decay in 76Ge. In view of the next generation of tonne-scale Ge-based 0νββ-decay searches that will probe the neutrino mass scale in the inverted-hierarchy region, a major goal of the MAJORANA DEMONSTRATOR is to demonstrate a path forward to achieving a background rate at or below 1 count/tonne/year in the 4 keV region of interest around the Q-value at 2039 keV. The background rejection techniques to be applied to the data include cuts based on data reduction, pulsemore » shape analysis, event coincidences, and time correlations. The Point Contact design of the DEMONSTRATOR's germanium detectors allows for significant reduction of gamma background.« less

A new variant of a scaling hypothesis and a fundamental equation of state based on it

NASA Astrophysics Data System (ADS)

Kudryavtseva, I. V.; Rykov, V. A.; Rykov, S. V.; Ustyuzhanin, E. E.

2018-01-01

This paper deals with a fundamental equation of state (FEOS) for substances. We have suggested a new method. It allows constructing FEOS that is based on the scaling theory of critical phenomena and describes thermodynamic properties related to liquid and gas phases of a substance in a wide range of the pressures and temperatures. In the framework of the methodological approach, we have provided: (i) a transition of FEOS in a virial equation of state in the low density region; (ii) a transition of FEOS in a Widom equation of state in the critical region. The method has been tested on the example of FEOS of R218. The area of applicability of FEOS is 0 < ρ/ρ c < 3.2 in the density and 133 < T < 440 K in the temperature. We have compared FEOS with some equations of state and discussed the results.

Regional 3D Numerical Modeling of the Lithosphere-Mantle System: Implications for Continental Rift-Parallel Surface Velocities

NASA Astrophysics Data System (ADS)

Stamps, S.; Bangerth, W.; Hager, B. H.

2014-12-01

The East African Rift System (EARS) is an active divergent plate boundary with slow, approximately E-W extension rates ranging from <1-6 mm/yr. Previous work using thin-sheet modeling indicates lithospheric buoyancy dominates the force balance driving large-scale Nubia-Somalia divergence, however GPS observations within the Western Branch of the EARS show along-rift motions that contradict this simple model. Here, we test the role of mantle flow at the rift-scale using our new, regional 3D numerical model based on the open-source code ASPECT. We define a thermal lithosphere with thicknesses that are systematically changed for generic models or based on geophysical constraints in the Western branch (e.g. melting depths, xenoliths, seismic tomography). Preliminary results suggest existing variations in lithospheric thicknesses along-rift in the Western Branch can drive upper mantle flow that is consistent with geodetic observations.

Two-way coupled SPH and particle level set fluid simulation.

PubMed

Losasso, Frank; Talton, Jerry; Kwatra, Nipun; Fedkiw, Ronald

2008-01-01

Grid-based methods have difficulty resolving features on or below the scale of the underlying grid. Although adaptive methods (e.g. RLE, octrees) can alleviate this to some degree, separate techniques are still required for simulating small-scale phenomena such as spray and foam, especially since these more diffuse materials typically behave quite differently than their denser counterparts. In this paper, we propose a two-way coupled simulation framework that uses the particle level set method to efficiently model dense liquid volumes and a smoothed particle hydrodynamics (SPH) method to simulate diffuse regions such as sprays. Our novel SPH method allows us to simulate both dense and diffuse water volumes, fully incorporates the particles that are automatically generated by the particle level set method in under-resolved regions, and allows for two way mixing between dense SPH volumes and grid-based liquid representations.

A hysteretic model considering Stribeck effect for small-scale magnetorheological damper

NASA Astrophysics Data System (ADS)

Zhao, Yu-Liang; Xu, Zhao-Dong

2018-06-01

Magnetorheological (MR) damper is an ideal semi-active control device for vibration suppression. The mechanical properties of this type of devices show strong nonlinear characteristics, especially the performance of the small-scale dampers. Therefore, developing an ideal model that can accurately describe the nonlinearity of such device is crucial to control design. In this paper, the dynamic characteristics of a small-scale MR damper developed by our research group is tested, and the Stribeck effect is observed in the low velocity region. Then, an improved model based on sigmoid model is proposed to describe this Stribeck effect observed in the experiment. After that, the parameters of this model are identified by genetic algorithms, and the mathematical relationship between these parameters and the input current, excitation frequency and amplitude is regressed. Finally, the predicted forces of the proposed model are validated with the experimental data. The results show that this model can well predict the mechanical properties of the small-scale damper, especially the Stribeck effect in the low velocity region.

Description of 'REQUEST-KYUSHYU' for KYUKEICHO regional data base

NASA Astrophysics Data System (ADS)

Takimoto, Shin'ichi

Kyushu Economic Research Association (a foundational juridical person) initiated the regional database services, ' REQUEST-Kyushu ' recently. It is the full scale databases compiled based on the information and know-hows which the Association has accumulated over forty years. It covers the regional information database for journal and newspaper articles, and statistical information database for economic statistics. As to the former database it is searched on a personal computer and then a search result (original text) is sent through a facsimile. As to the latter, it is also searched on a personal computer where the data is processed, edited or downloaded. This paper describes characteristics, content and the system outline of 'REQUEST-Kyushu'.

Multiscale object-based drought monitoring and comparison in rainfed and irrigated agriculture from Landsat 8 OLI imagery

NASA Astrophysics Data System (ADS)

Ozelkan, Emre; Chen, Gang; Ustundag, Burak Berk

2016-02-01

Drought is a rapidly rising environmental issue that can cause hardly repaired or unrepaired damages to the nature and socio-economy. This is especially true for a region that features arid/semi-arid climate, including the Turkey's most important agricultural district - Southeast Anatolia. In this area, we examined the uncertainties of applying Landsat 8 Operational Land Imager (OLI) NDVI data to estimate meteorological drought - Standardized Precipitation Index (SPI) - measured from 31 in-situ agro-meteorological monitoring stations during spring and summer of 2013 and 2014. Our analysis was designed to address two important, yet under-examined questions: (i) how does the co-existence of rainfed and irrigated agriculture affect remote sensing drought monitoring in an arid/semi-arid region? (ii) What is the role of spatial scale in drought monitoring using a GEOBIA (geographic object-based image analysis) framework? Results show that spatial scale exerted a higher impact on drought monitoring especially in the drier year 2013, during which small scales were found to outperform large scales in general. In addition, consideration of irrigated and rainfed areas separately ensured a better performance in drought analysis. Compared to the positive correlations between SPI and NDVI over the rainfed areas, negative correlations were determined over the irrigated agricultural areas. Finally, the time lag effect was evident in the study, i.e., strong correlations between spring SPI and summer NDVI in both 2013 and 2014. This reflects the fact that spring watering is crucial for the growth and yield of the major crops (i.e., winter wheat, barley and lentil) cultivated in the region.

A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity

NASA Astrophysics Data System (ADS)

Rune Karlsen, Stein; Anderson, Helen B.; van der Wal, René; Bremset Hansen, Brage

2018-02-01

Efforts to estimate plant productivity using satellite data can be frustrated by the presence of cloud cover. We developed a new method to overcome this problem, focussing on the high-arctic archipelago of Svalbard where extensive cloud cover during the growing season can prevent plant productivity from being estimated over large areas. We used a field-based time-series (2000-2009) of live aboveground vascular plant biomass data and a recently processed cloud-free MODIS-Normalised Difference Vegetation Index (NDVI) data set (2000-2014) to estimate, on a pixel-by-pixel basis, the onset of plant growth. We then summed NDVI values from onset of spring to the average time of peak NDVI to give an estimate of annual plant productivity. This remotely sensed productivity measure was then compared, at two different spatial scales, with the peak plant biomass field data. At both the local scale, surrounding the field data site, and the larger regional scale, our NDVI measure was found to predict plant biomass (adjusted R 2 = 0.51 and 0.44, respectively). The commonly used ‘maximum NDVI’ plant productivity index showed no relationship with plant biomass, likely due to some years having very few cloud-free images available during the peak plant growing season. Thus, we propose this new summed NDVI from onset of spring to time of peak NDVI as a proxy of large-scale plant productivity for regions such as the Arctic where climatic conditions restrict the availability of cloud-free images.

[Spatial temporal differentiation of product-based and consumption-based CO2 emissions and balance in the Beijing-Tianjin-Hebei region: an economic input- output analysis].

PubMed

Wang, Hao; Chen, Cao-cao; Pan, Tao; Liu, Chun-lan; Chen, Long; Sun, Li

2014-09-01

Distinguishing product-based and consumption-based CO2 emissions in the open economic region is the basis for differentiating the emission responsibility, which is attracting increasing attention of decision-makers'attention. The spatial and temporal characteristics of product-based and consumption-based CO2 emissions, as well as carbon balance, in 1997, 2002 and 2007 of JING- JIN-JI region were analyzed by the Economic Input-Output-Life Cycle Assessment model. The results revealed that both the product- based and consumption-based CO2 emissions in the region have been increased by about 4% annually. The percentage of CO2 emissions embodied in trade was 30% -83% , to which the domestic trading added the most. The territorial and consumption-based CO2 emissions in Hebei province were the predominant emission in JING-JIN-JI region, and the increasing speed and emission intensity were stronger than those of Beijing and Tianjin. JING-JIN-JI region was a net inflow region of CO2 emissions, and parts of the emission responsibility were transferred. Beijing and Tianjin were the net importers of CO2 emissions, and Hebei was a net outflow area of CO2 emissions. The key CO2 emission departments in the region were concentrated, and the similarity was great. The inter-regional mechanisms could be set up for joint prevention and control work. - Production and distribution of electricity, gas and water and smelting and pressing of metals had the highest reliability on CO2 emissions, and took on the responsibility of other departments. The EIO-LCA model could be used to analyze the product-based and consumption-based CO2 emissions, which is helpful for the delicate management of regional CO2 emissions reduction and policies making, and stimulating the reduction cooperation at regional scale.

Fire frequency in the Interior Columbia River Basin: Building regional models from fire history data

USGS Publications Warehouse

McKenzie, D.; Peterson, D.L.; Agee, James K.

2000-01-01

Fire frequency affects vegetation composition and successional pathways; thus it is essential to understand fire regimes in order to manage natural resources at broad spatial scales. Fire history data are lacking for many regions for which fire management decisions are being made, so models are needed to estimate past fire frequency where local data are not yet available. We developed multiple regression models and tree-based (classification and regression tree, or CART) models to predict fire return intervals across the interior Columbia River basin at 1-km resolution, using georeferenced fire history, potential vegetation, cover type, and precipitation databases. The models combined semiqualitative methods and rigorous statistics. The fire history data are of uneven quality; some estimates are based on only one tree, and many are not cross-dated. Therefore, we weighted the models based on data quality and performed a sensitivity analysis of the effects on the models of estimation errors that are due to lack of cross-dating. The regression models predict fire return intervals from 1 to 375 yr for forested areas, whereas the tree-based models predict a range of 8 to 150 yr. Both types of models predict latitudinal and elevational gradients of increasing fire return intervals. Examination of regional-scale output suggests that, although the tree-based models explain more of the variation in the original data, the regression models are less likely to produce extrapolation errors. Thus, the models serve complementary purposes in elucidating the relationships among fire frequency, the predictor variables, and spatial scale. The models can provide local managers with quantitative information and provide data to initialize coarse-scale fire-effects models, although predictions for individual sites should be treated with caution because of the varying quality and uneven spatial coverage of the fire history database. The models also demonstrate the integration of qualitative and quantitative methods when requisite data for fully quantitative models are unavailable. They can be tested by comparing new, independent fire history reconstructions against their predictions and can be continually updated, as better fire history data become available.

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers

PubMed Central

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell’Aquila, Alessandro

2014-01-01

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests. PMID:24706833

Comparison of Multi-Scale Digital Elevation Models for Defining Waterways and Catchments Over Large Areas

NASA Astrophysics Data System (ADS)

Harris, B.; McDougall, K.; Barry, M.

2012-07-01

Digital Elevation Models (DEMs) allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS) techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment) including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas) are adequate for the creation of waterways and catchments at a regional scale.

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers.

PubMed

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell'Aquila, Alessandro

2014-04-15

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests.

A map of human impacts to a ``pristine'' coral reef ecosystem, the Papahānaumokuākea Marine National Monument

NASA Astrophysics Data System (ADS)

Selkoe, K. A.; Halpern, B. S.; Ebert, C. M.; Franklin, E. C.; Selig, E. R.; Casey, K. S.; Bruno, J.; Toonen, R. J.

2009-09-01

Effective and comprehensive regional-scale marine conservation requires fine-grained data on the spatial patterns of threats and their overlap. To address this need for the Papahānaumokuākea Marine National Monument (Monument) in Hawaii, USA, spatial data on 14 recent anthropogenic threats specific to this region were gathered or created, including alien species, bottom fishing, lobster trap fishing, ship-based pollution, ship strike risks, marine debris, research diving, research equipment installation, research wildlife sacrifice, and several anthropogenic climate change threats i.e., increase in ultraviolet (UV) radiation, seawater acidification, the number of warm ocean temperature anomalies relevant to disease outbreaks and coral bleaching, and sea level rise. These data were combined with habitat maps and expert judgment on the vulnerability of different habitat types in the Monument to estimate spatial patterns of current cumulative impact at 1 ha (0.01 km2) resolution. Cumulative impact was greatest for shallow reef areas and peaked at Maro Reef, where 13 of the 14 threats overlapped in places. Ocean temperature variation associated with disease outbreaks was found to have the highest predicted impact overall, followed closely by other climate-related threats, none of which have easily tractable management solutions at the regional scale. High impact threats most tractable to regional management relate to ship traffic. Sensitivity analyses show that the results are robust to both data availability and quality. Managers can use these maps to (1) inform management and surveillance priorities based on the ranking of threats and their distributions, (2) guide permitting decisions based on cumulative impacts, and (3) choose areas to monitor for climate change effects. Furthermore, this regional analysis can serve as a case study for managers elsewhere interested in assessing and mapping region-specific cumulative human impacts.

Wetlands as large-scale nature-based solutions: status and future challenges for research and management

NASA Astrophysics Data System (ADS)

Thorslund, Josefin; Jarsjö, Jerker; Destouni, Georgia

2017-04-01

Wetlands are often considered as nature-based solutions that can provide a multitude of services of great social, economic and environmental value to humankind. The services may include recreation, greenhouse gas sequestration, contaminant retention, coastal protection, groundwater level and soil moisture regulation, flood regulation and biodiversity support. Changes in land-use, water use and climate can all impact wetland functions and occur at scales extending well beyond the local scale of an individual wetland. However, in practical applications, management decisions usually regard and focus on individual wetland sites and local conditions. To understand the potential usefulness and services of wetlands as larger-scale nature-based solutions, e.g. for mitigating negative impacts from large-scale change pressures, one needs to understand the combined function multiple wetlands at the relevant large scales. We here systematically investigate if and to what extent research so far has addressed the large-scale dynamics of landscape systems with multiple wetlands, which are likely to be relevant for understanding impacts of regional to global change. Our investigation regards key changes and impacts of relevance for nature-based solutions, such as large-scale nutrient and pollution retention, flow regulation and coastal protection. Although such large-scale knowledge is still limited, evidence suggests that the aggregated functions and effects of multiple wetlands in the landscape can differ considerably from those observed at individual wetlands. Such scale differences may have important implications for wetland function-effect predictability and management under large-scale change pressures and impacts, such as those of climate change.

Water Resources Implications of Cellulosic Biofuel Production at a Regional Scale

NASA Astrophysics Data System (ADS)

Christopher, S. F.; Schoenholtz, S. H.; Nettles, J. E.

2011-12-01

Recent increases in oil prices, a strong national interest in greater energy independence, and a concern for the role of fossil fuels in global climate change, have led to a dramatic expansion in use of alternative renewable energy sources in the U.S. The U.S. government has mandated production of 36 billion gallons of renewable fuels by 2022, of which 16 billion gallons are required to be cellulosic biofuels. Production of cellulosic biomass offers a promising alternative to corn-based systems because large-scale production of corn-based ethanol often requires irrigation and is associated with increased erosion, excess sediment export, and enhanced leaching of nitrogen and phosphorus. Although cultivation of switchgrass using standard agricultural practices is one option being considered for production of cellulosic biomass, intercropping cellulosic biofuel crops within managed forests could provide feedstock without primary land use change or the water quality impacts associated with annual crops. Catchlight Energy LLC is examining the feasibility and sustainability of intercropping switchgrass in loblolly pine plantations in the southeastern U.S. Ongoing research is determining efficient operational techniques and information needed to evaluate effects of these practices on water resources in small watershed-scale (~25 ha) studies. Three sets of four to five sub-watersheds are fully instrumented and currently collecting calibration data in North Carolina, Alabama, and Mississippi. These watershed studies will provide detailed information to understand processes and guide management decisions. However, environmental implications of cellulosic systems need to be examined at a regional scale. We used the Soil Water Assessment Tool (SWAT), a physically-based hydrologic model, to examine water quantity effects of various land use change scenarios ranging from switchgrass intercropping a small percentage of managed pine forest land to conversion of all managed forested land to switchgrass. The regional-scale SWAT model was successfully run and calibrated on the ~ 5 million ha Tombigbee Watershed located in Mississippi and Alabama. Publically available datasets were used as input to the model and for calibration. To improve calibration statistics, five tree age classes (0-4 yr, 4-10 yr, 10-17 yr, 17-24 yr, 24-30 yr) were added to the model to more appropriately represent existing forested systems in the region, which are not included within the standard SWAT set-up. Our results will be essential to public policy makers as they influence and plan for large-scale production of cellulosic biofuels, while sustaining water quality and quantity.

Pattern-based, multi-scale segmentation and regionalization of EOSD land cover

NASA Astrophysics Data System (ADS)

Niesterowicz, Jacek; Stepinski, Tomasz F.

2017-10-01

The Earth Observation for Sustainable Development of Forests (EOSD) map is a 25 m resolution thematic map of Canadian forests. Because of its large spatial extent and relatively high resolution the EOSD is difficult to analyze using standard GIS methods. In this paper we propose multi-scale segmentation and regionalization of EOSD as new methods for analyzing EOSD on large spatial scales. Segments, which we refer to as forest land units (FLUs), are delineated as tracts of forest characterized by cohesive patterns of EOSD categories; we delineated from 727 to 91,885 FLUs within the spatial extent of EOSD depending on the selected scale of a pattern. Pattern of EOSD's categories within each FLU is described by 1037 landscape metrics. A shapefile containing boundaries of all FLUs together with an attribute table listing landscape metrics make up an SQL-searchable spatial database providing detailed information on composition and pattern of land cover types in Canadian forest. Shapefile format and extensive attribute table pertaining to the entire legend of EOSD are designed to facilitate broad range of investigations in which assessment of composition and pattern of forest over large areas is needed. We calculated four such databases using different spatial scales of pattern. We illustrate the use of FLU database for producing forest regionalization maps of two Canadian provinces, Quebec and Ontario. Such maps capture the broad scale variability of forest at the spatial scale of the entire province. We also demonstrate how FLU database can be used to map variability of landscape metrics, and thus the character of landscape, over the entire Canada.

Dark and Bright Terrains of Pluto

NASA Image and Video Library

2015-07-10

These circular maps shows the distribution of Pluto's dark and bright terrains as revealed by NASA's New Horizons mission prior to July 4, 2015. Each map is an azimuthal equidistant projection centered on the north pole, with latitude and longitude indicated. Both a gray-scale and color version are shown. The gray-scale version is based on 7 days of panchromatic imaging from the Long Range Reconnaissance Imager (LORRI), whereas the color version uses the gray-scale base and incorporates lower-resolution color information from the Multi-spectral Visible Imaging Camera (MVIC), part of the Ralph instrument. The color version is also shown in a simple cylindrical projection in PIA19700. In these maps, the polar bright terrain is surrounded by a somewhat darker polar fringe, one whose latitudinal position varies strongly with longitude. Especially striking are the much darker regions along the equator. A broad dark swath ("the whale") stretches along the equator from approximately 20 to 160 degrees of longitude. Several dark patches appear in a regular sequence centered near 345 degrees of longitude. A spectacular bright region occupies Pluto's mid-latitudes near 180 degrees of longitude, and stretches southward over the equator. New Horizons' closest approach to Pluto will occur near this longitude, which will permit high-resolution visible imaging and compositional mapping of these various regions. http://photojournal.jpl.nasa.gov/catalog/PIA19706

Improving Global Forecast System of extreme precipitation events with regional statistical model: Application of quantile-based probabilistic forecasts

NASA Astrophysics Data System (ADS)

Shastri, Hiteshri; Ghosh, Subimal; Karmakar, Subhankar

2017-02-01

Forecasting of extreme precipitation events at a regional scale is of high importance due to their severe impacts on society. The impacts are stronger in urban regions due to high flood potential as well high population density leading to high vulnerability. Although significant scientific improvements took place in the global models for weather forecasting, they are still not adequate at a regional scale (e.g., for an urban region) with high false alarms and low detection. There has been a need to improve the weather forecast skill at a local scale with probabilistic outcome. Here we develop a methodology with quantile regression, where the reliably simulated variables from Global Forecast System are used as predictors and different quantiles of rainfall are generated corresponding to that set of predictors. We apply this method to a flood-prone coastal city of India, Mumbai, which has experienced severe floods in recent years. We find significant improvements in the forecast with high detection and skill scores. We apply the methodology to 10 ensemble members of Global Ensemble Forecast System and find a reduction in ensemble uncertainty of precipitation across realizations with respect to that of original precipitation forecasts. We validate our model for the monsoon season of 2006 and 2007, which are independent of the training/calibration data set used in the study. We find promising results and emphasize to implement such data-driven methods for a better probabilistic forecast at an urban scale primarily for an early flood warning.

Indicators of wetland condition for the prairie pothole region of the United States.

PubMed

Guntenspergen, G R; Peterson, S A; Leibowitz, S G; Cowardin, L M

2002-09-01

We describe a study designed to evaluate the performance of wetland condition indicators of the Prairie Pothole Region (PPR) of the north central United States. Basin and landscape scale indicators were tested in 1992 and 1993 to determine their ability to discriminate between the influences of grassland dominated and cropland dominated landscapes in the PPR. Paired plots were selected from each of the major regions of the PPR. Among the landscape scale indicators tested, those most capable of distinguishing between the two landscapes were: 1) frequency of drained wetland basins. 2) total length of drainage ditch per plot, 3) amount of exposed soil in the upland subject to erosion, 4) indices of change in area of wetland covered by water, and 5) number of breeding duck pairs. Basin scale indicators including soil phosphorus concentrations and invertebrate taxa richness showed some promise: however, plant species richness was the only statistically significant basin scale indicator distinguishing grassland dominated from cropland dominated landscapes. Although our study found a number of promising candidate indicators, one of our conclusions is that basin scale indicators present a number of implementation problems. including: skill level requirements, site access denials, and recession of site access by landowners. Alternatively, we suggest that the use of landscape indicators based on remote sensing can be an effective means of assessing wetland integrity.

Comparison of three GIS-based models for predicting rockfall runout zones at a regional scale

NASA Astrophysics Data System (ADS)

Dorren, Luuk K. A.; Seijmonsbergen, Arie C.

2003-11-01

Site-specific information about the level of protection that mountain forests provide is often not available for large regions. Information regarding rockfalls is especially scarce. The most efficient way to obtain information about rockfall activity and the efficacy of protection forests at a regional scale is to use a simulation model. At present, it is still unknown which forest parameters could be incorporated best in such models. Therefore, the purpose of this study was to test and evaluate a model for rockfall assessment at a regional scale in which simple forest stand parameters, such as the number of trees per hectare and the diameter at breast height, are incorporated. Therefore, a newly developed Geographical Information System (GIS)-based distributed model is compared with two existing rockfall models. The developed model is the only model that calculates the rockfall velocity on the basis of energy loss due to collisions with trees and on the soil surface. The two existing models calculate energy loss over the distance between two cell centres, while the newly developed model is able to calculate multiple bounces within a pixel. The patterns of rockfall runout zones produced by the three models are compared with patterns of rockfall deposits derived from geomorphological field maps. Furthermore, the rockfall velocities modelled by the three models are compared. It is found that the models produced rockfall runout zone maps with rather similar accuracies. However, the developed model performs best on forested hillslopes and it also produces velocities that match best with field estimates on both forested and nonforested hillslopes irrespective of the slope gradient.

A “Fork-to-Farm” Multi-Scale Approach to Promote Sustainable Food Systems for Nutrition and Health: A Perspective for the Mediterranean Region

PubMed Central

Verger, Eric O.; Perignon, Marlene; El Ati, Jalila; Darmon, Nicole; Dop, Marie-Claude; Drogué, Sophie; Dury, Sandrine; Gaillard, Cédric; Sinfort, Carole; Amiot, Marie-Josèphe; Amiot, Marie-Josèphe

2018-01-01

Mediterranean countries are undergoing dietary and nutritional changes that affect their inhabitants' health, while facing massive environmental challenges. The increasing demand of water in agriculture, the capacity to maintain local food production, and the growing dependence on food imports are interconnected issues that must be addressed to ensure food security and nutrition in the Mediterranean region. Here, we present the conceptual framework and methodologies developed by the MEDINA-Study Group for rethinking food systems toward sustainable consumption and production modes. Based on its multidisciplinary expertise, the MEDINA-Study Group designed a “fork-to-farm” multi-scale approach, stemming from current dietary habits and examining how some options to nutritionally improve these habits might affect the food systems. This approach was developed for research activities in the South of France and Tunisia, two areas with very different diet-agriculture-environment nexus. The conceptual framework is based on the analysis of elements of the food systems (from consumption to production) at different levels (individual, household, regional and national levels). The methods include: (i) modeling options of dietary changes at different scales, in order to nutritionally optimize food consumption-production without increasing the environmental impact, (ii) translating the best-choice changes into possible policy actions, (iii) testing the acceptability and feasibility of these actions with several stakeholders, and (iv) producing guidelines for sustainable food choices and production. The MEDINA-Study Group identified additional issues that could be included in a future framework to help designing ambitious agricultural, food and health policies in the Mediterranean region. PMID:29872660

Spatiotemporal Variations in the Difference between Satellite-observed Land Surface Temperature and Station-based Near-surface Air Temperature

NASA Astrophysics Data System (ADS)

Lian, X.

2016-12-01

There is an increasing demand to integrate land surface temperature (LST) into climate research due to its global coverage, which requires a comprehensive knowledge of its distinctive characteristics compared to near-surface air temperature ( ). Using satellite observations and in-situ station-based datasets, we conducted a global-scale assessment of the spatial, seasonal, and interannual variations in the difference between daytime maximum LST and daytime maximum ( , LST - ) during 2003-2014. Spatially, LST is generally higher than over arid and sparsely vegetated regions in the mid-low latitudes, but LST is lower than in the tropical rainforests due to strong evaporative cooling, and in the high-latitude regions due to snow-induced radiative cooling. Seasonally, is negative in tropical regions throughout the year, while it displays a pronounced seasonality in both the mid-latitudes and boreal regions. The seasonality in the mid-latitudes is a result of the asynchronous responses of LST and to the seasonal cycle of radiation and vegetation abundance, whereas in the boreal regions, seasonality is mainly caused by the change in snow cover. At an interannual scale, only a small proportion of the land surface displays a statistically significant trend (P <0.05) due to the short time span of current measurements. Our study identified substantial spatial heterogeneity and seasonality in , as well as its determinant environmental drivers, and thus provides a useful reference for monitoring near-surface temperature changes using remote sensing, particularly in remote regions.

Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

NASA Astrophysics Data System (ADS)

Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

2013-12-01

Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output fields to facilitate daily mapping of fluxes at sub-field scales. A complete processing infrastructure to automatically ingest and pre-process all required input data and to execute the integrated modeling system for near real-time agricultural monitoring purposes over targeted MENA sites is being developed, and initial results from this concerted effort will be discussed.

Status of the Majorana Demonstrator

DOE PAGES

Cuesta, C.; Abgrall, N.; Arnquist, I. J.; ...

2015-08-06

In this study, the Majorana Collaboration is constructing the Majorana Demonstrator, an ultra-low background, 40-kg modular high purity Ge detector array to search for neutrinoless double-beta decay in 76Ge. In view of the next generation of tonne-scale Ge-based neutrinoless double-beta decay searches that will probe the neutrino mass scale in the inverted-hierarchy region, a major goal of the Demonstrator is to demonstrate a path forward to achieving a background rate at or below 1 count/tonne/year in the 4 keV region of interest around the Q-value at 2039 keV. Lastly, the current status of the Demonstrator is discussed, as are plansmore » for its completion.« less

Rockfall hazard and risk assessments along roads at a regional scale: example in Swiss Alps

NASA Astrophysics Data System (ADS)

Michoud, C.; Derron, M.-H.; Horton, P.; Jaboyedoff, M.; Baillifard, F.-J.; Loye, A.; Nicolet, P.; Pedrazzini, A.; Queyrel, A.

2012-03-01

Unlike fragmental rockfall runout assessments, there are only few robust methods to quantify rock-mass-failure susceptibilities at regional scale. A detailed slope angle analysis of recent Digital Elevation Models (DEM) can be used to detect potential rockfall source areas, thanks to the Slope Angle Distribution procedure. However, this method does not provide any information on block-release frequencies inside identified areas. The present paper adds to the Slope Angle Distribution of cliffs unit its normalized cumulative distribution function. This improvement is assimilated to a quantitative weighting of slope angles, introducing rock-mass-failure susceptibilities inside rockfall source areas previously detected. Then rockfall runout assessment is performed using the GIS- and process-based software Flow-R, providing relative frequencies for runout. Thus, taking into consideration both susceptibility results, this approach can be used to establish, after calibration, hazard and risk maps at regional scale. As an example, a risk analysis of vehicle traffic exposed to rockfalls is performed along the main roads of the Swiss alpine valley of Bagnes.

Visualization and Analysis of Multi-scale Land Surface Products via Giovanni Portals

NASA Technical Reports Server (NTRS)

Shen, Suhung; Kempler, Steven J.; Gerasimov, Irina V.

2013-01-01

Large volumes of MODIS land data products at multiple spatial resolutions have been integrated into the Giovanni online analysis system to support studies on land cover and land use changes,focused on the Northern Eurasia and Monsoon Asia regions through the LCLUC program. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data.Customized Giovanni Web portals (Giovanni-NEESPI andGiovanni-MAIRS) have been created to integrate land, atmospheric,cryospheric, and societal products, enabling researchers to do quick exploration and basic analyses of land surface changes, and their relationships to climate, at global and regional scales. This presentation shows a sample Giovanni portal page, lists selected data products in the system, and illustrates potential analyses with imagesand time-series at global and regional scales, focusing on climatology and anomaly analysis. More information is available at the GES DISCMAIRS data support project portal: http:disc.sci.gsfc.nasa.govmairs.

Automated detection of microaneurysms using scale-adapted blob analysis and semi-supervised learning.

PubMed

Adal, Kedir M; Sidibé, Désiré; Ali, Sharib; Chaum, Edward; Karnowski, Thomas P; Mériaudeau, Fabrice

2014-04-01

Despite several attempts, automated detection of microaneurysm (MA) from digital fundus images still remains to be an open issue. This is due to the subtle nature of MAs against the surrounding tissues. In this paper, the microaneurysm detection problem is modeled as finding interest regions or blobs from an image and an automatic local-scale selection technique is presented. Several scale-adapted region descriptors are introduced to characterize these blob regions. A semi-supervised based learning approach, which requires few manually annotated learning examples, is also proposed to train a classifier which can detect true MAs. The developed system is built using only few manually labeled and a large number of unlabeled retinal color fundus images. The performance of the overall system is evaluated on Retinopathy Online Challenge (ROC) competition database. A competition performance measure (CPM) of 0.364 shows the competitiveness of the proposed system against state-of-the art techniques as well as the applicability of the proposed features to analyze fundus images. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Satellite data based method for general survey of forest insect disturbance in British Columbia

NASA Astrophysics Data System (ADS)

Ranson, J.; Montesano, P.

2008-12-01

Regional forest disturbances caused by insects are important to monitor and quantify because of their influence on local ecosystems and the global carbon cycle. Local damage to forest trees disrupts food supplies and shelter for a variety of organisms. Changes in the global carbon budget, its sources and its sinks affect the way the earth functions as a whole, and has an impact on global climate. Furthermore, the ability to detect nascent outbreaks and monitor the spread of regional infestations helps managers mitigate the damage done by catastrophic insect outbreaks. While detection is needed at a fine scale to support local mitigation efforts, detection at a broad regional scale is important for carbon flux modeling on the landscape scale, and needed to direct the local efforts. This paper presents a method for routinely detecting insect damage to coniferous forests using MODIS vegetation indices, thermal anomalies and land cover. The technique is validated using insect outbreak maps and accounts for fire disturbance effects. The range of damage detected may be used to interpret and quantify possible forest damage by insects.

Multi-Scale Drought Analysis using Thermal Remote Sensing: A Case Study in Georgia’s Altamaha River Watershed

NASA Astrophysics Data System (ADS)

Jacobs, J. M.; Bhat, S.; Choi, M.; Mecikalski, J. R.; Anderson, M. C.

2009-12-01

The unprecedented recent droughts in the Southeast US caused reservoir levels to drop dangerously low, elevated wildfire hazard risks, reduced hydropower generation and caused severe economic hardships. Most drought indices are based on recent rainfall or changes in vegetation condition. However in heterogeneous landscapes, soils and vegetation (type and cover) combine to differentially stress regions even under similar weather conditions. This is particularly true for the heterogeneous landscapes and highly variable rainfall in the Southeastern United States. This research examines the spatiotemperal evolution of watershed scale drought using a remotely sensed stress index. Using thermal-infrared imagery, a fully automated inverse model of Atmosphere-Land Exchange (ALEXI), GIS datasets and analysis tools, modeled daily surface moisture stress is examined at a 10-km resolution grid covering central to southern Georgia. Regional results are presented for the 2000-2008 period. The ALEXI evaporative stress index (ESI) is compared to existing regional drought products and validated using local hydrologic measurements in Georgia’s Altamaha River watershed at scales from 10 to 10,000 km2.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

Non-destructive evaluation of laboratory scale hydraulic fracturing using acoustic emission

NASA Astrophysics Data System (ADS)

Hampton, Jesse Clay

The primary objective of this research is to develop techniques to characterize hydraulic fractures and fracturing processes using acoustic emission monitoring based on laboratory scale hydraulic fracturing experiments. Individual microcrack AE source characterization is performed to understand the failure mechanisms associated with small failures along pre-existing discontinuities and grain boundaries. Individual microcrack analysis methods include moment tensor inversion techniques to elucidate the mode of failure, crack slip and crack normal direction vectors, and relative volumetric deformation of an individual microcrack. Differentiation between individual microcrack analysis and AE cloud based techniques is studied in efforts to refine discrete fracture network (DFN) creation and regional damage quantification of densely fractured media. Regional damage estimations from combinations of individual microcrack analyses and AE cloud density plotting are used to investigate the usefulness of weighting cloud based AE analysis techniques with microcrack source data. Two granite types were used in several sample configurations including multi-block systems. Laboratory hydraulic fracturing was performed with sample sizes ranging from 15 x 15 x 25 cm3 to 30 x 30 x 25 cm 3 in both unconfined and true-triaxially confined stress states using different types of materials. Hydraulic fracture testing in rock block systems containing a large natural fracture was investigated in terms of AE response throughout fracture interactions. Investigations of differing scale analyses showed the usefulness of individual microcrack characterization as well as DFN and cloud based techniques. Individual microcrack characterization weighting cloud based techniques correlated well with post-test damage evaluations.

Toward Improved Parameterization of a Meso-Scale Hydrologic Model in a Discontinuous Permafrost, Boreal Forest Ecosystem

NASA Astrophysics Data System (ADS)

Endalamaw, A. M.; Bolton, W. R.; Young, J. M.; Morton, D.; Hinzman, L. D.

2013-12-01

The sub-arctic environment can be characterized as being located in the zone of discontinuous permafrost. Although the distribution of permafrost is site specific, it dominates many of the hydrologic and ecologic responses and functions including vegetation distribution, stream flow, soil moisture, and storage processes. In this region, the boundaries that separate the major ecosystem types (deciduous dominated and coniferous dominated ecosystems) as well as permafrost (permafrost verses non-permafrost) occur over very short spatial scales. One of the goals of this research project is to improve parameterizations of meso-scale hydrologic models in this environment. Using the Caribou-Poker Creeks Research Watershed (CPCRW) as the test area, simulations of the headwater catchments of varying permafrost and vegetation distributions were performed. CPCRW, located approximately 50 km northeast of Fairbanks, Alaska, is located within the zone of discontinuous permafrost and the boreal forest ecosystem. The Variable Infiltration Capacity (VIC) model was selected as the hydrologic model. In CPCRW, permafrost and coniferous vegetation is generally found on north facing slopes and valley bottoms. Permafrost free soils and deciduous vegetation is generally found on south facing slopes. In this study, hydrologic simulations using fine scale vegetation and soil parameterizations - based upon slope and aspect analysis at a 50 meter resolution - were conducted. Simulations were also conducted using downscaled vegetation from the Scenarios Network for Alaska and Arctic Planning (SNAP) (1 km resolution) and soil data sets from the Food and Agriculture Organization (FAO) (approximately 9 km resolution). Preliminary simulation results show that soil and vegetation parameterizations based upon fine scale slope/aspect analysis increases the R2 values (0.5 to 0.65 in the high permafrost (53%) basin; 0.43 to 0.56 in the low permafrost (2%) basin) relative to parameterization based on coarse scale data. These results suggest that using fine resolution parameterizations can be used to improve meso-scale hydrological modeling in this region.

How do large-scale agricultural investments affect land use and the environment on the western slopes of Mount Kenya? Empirical evidence based on small-scale farmers' perceptions and remote sensing.

PubMed

Zaehringer, Julie G; Wambugu, Grace; Kiteme, Boniface; Eckert, Sandra

2018-05-01

Africa has been heavily targeted by large-scale agricultural investments (LAIs) throughout the last decade, with scarcely known impacts on local social-ecological systems. In Kenya, a large number of LAIs were made in the region northwest of Mount Kenya. These large-scale farms produce vegetables and flowers mainly for European markets. However, land use in the region remains dominated by small-scale crop and livestock farms with less than 1 ha of land each, who produce both for their own subsistence and for the local markets. We interviewed 100 small-scale farmers living near five different LAIs to elicit their perceptions of the impacts that these LAIs have on their land use and the overall environment. Furthermore, we analyzed remotely sensed land cover and land use data to assess land use change in the vicinity of the five LAIs. While land use change did not follow a clear trend, a number of small-scale farmers did adapt their crop management to environmental changes such as a reduced river water flows and increased pests, which they attributed to the presence of LAIs. Despite the high number of open conflicts between small-scale land users and LAIs around the issue of river water abstraction, the main environmental impact, felt by almost half of the interviewed land users, was air pollution with agrochemicals sprayed on the LAIs' land. Even though only a low percentage of local land users and their household members were directly involved with LAIs, a large majority of respondents favored the presence of LAIs nearby, as they are believed to contribute to the region's overall economic development. Copyright © 2018 Elsevier Ltd. All rights reserved.

Distinct patterns of brain atrophy in Genetic Frontotemporal Dementia Initiative (GENFI) cohort revealed by visual rating scales.

PubMed

Fumagalli, Giorgio G; Basilico, Paola; Arighi, Andrea; Bocchetta, Martina; Dick, Katrina M; Cash, David M; Harding, Sophie; Mercurio, Matteo; Fenoglio, Chiara; Pietroboni, Anna M; Ghezzi, Laura; van Swieten, John; Borroni, Barbara; de Mendonça, Alexandre; Masellis, Mario; Tartaglia, Maria C; Rowe, James B; Graff, Caroline; Tagliavini, Fabrizio; Frisoni, Giovanni B; Laforce, Robert; Finger, Elizabeth; Sorbi, Sandro; Scarpini, Elio; Rohrer, Jonathan D; Galimberti, Daniela

2018-05-24

In patients with frontotemporal dementia, it has been shown that brain atrophy occurs earliest in the anterior cingulate, insula and frontal lobes. We used visual rating scales to investigate whether identifying atrophy in these areas may be helpful in distinguishing symptomatic patients carrying different causal mutations in the microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame (C9ORF72) genes. We also analysed asymptomatic carriers to see whether it was possible to visually identify brain atrophy before the appearance of symptoms. Magnetic resonance imaging of 343 subjects (63 symptomatic mutation carriers, 132 presymptomatic mutation carriers and 148 control subjects) from the Genetic Frontotemporal Dementia Initiative study were analysed by two trained raters using a protocol of six visual rating scales that identified atrophy in key regions of the brain (orbitofrontal, anterior cingulate, frontoinsula, anterior and medial temporal lobes and posterior cortical areas). Intra- and interrater agreement were greater than 0.73 for all the scales. Voxel-based morphometric analysis demonstrated a strong correlation between the visual rating scale scores and grey matter atrophy in the same region for each of the scales. Typical patterns of atrophy were identified: symmetric anterior and medial temporal lobe involvement for MAPT, asymmetric frontal and parietal loss for GRN, and a more widespread pattern for C9ORF72. Presymptomatic MAPT carriers showed greater atrophy in the medial temporal region than control subjects, but the visual rating scales could not identify presymptomatic atrophy in GRN or C9ORF72 carriers. These simple-to-use and reproducible scales may be useful tools in the clinical setting for the discrimination of different mutations of frontotemporal dementia, and they may even help to identify atrophy prior to onset in those with MAPT mutations.

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

NASA Astrophysics Data System (ADS)

Zhu, Hongchun; Zhao, Yipeng; Liu, Haiying

2018-04-01

Scale is the basic attribute for expressing and describing spatial entity and phenomena. It offers theoretical significance in the study of gully structure information, variable characteristics of watershed morphology, and development evolution at different scales. This research selected five different areas in China's Loess Plateau as the experimental region and used DEM data at different scales as the experimental data. First, the change rule of the characteristic parameters of the data at different scales was analyzed. The watershed structure information did not change along with a change in the data scale. This condition was proven by selecting indices of gully bifurcation ratio and fractal dimension as characteristic parameters of watershed structure information. Then, the change rule of the characteristic parameters of gully structure with different analysis scales was analyzed by setting the scale sequence of analysis at the extraction gully. The gully structure of the watershed changed with variations in the analysis scale, and the change rule was obvious when the gully level changed. Finally, the change rule of the characteristic parameters of the gully structure at different areas was analyzed. The gully fractal dimension showed a significant numerical difference in different areas, whereas the variation of the gully branch ratio was small. The change rule indicated that the development degree of the gully obviously varied in different regions, but the morphological structure was basically similar.

Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models

NASA Astrophysics Data System (ADS)

Zhu, Hongchun; Zhao, Yipeng; Liu, Haiying

2018-06-01

Scale is the basic attribute for expressing and describing spatial entity and phenomena. It offers theoretical significance in the study of gully structure information, variable characteristics of watershed morphology, and development evolution at different scales. This research selected five different areas in China's Loess Plateau as the experimental region and used DEM data at different scales as the experimental data. First, the change rule of the characteristic parameters of the data at different scales was analyzed. The watershed structure information did not change along with a change in the data scale. This condition was proven by selecting indices of gully bifurcation ratio and fractal dimension as characteristic parameters of watershed structure information. Then, the change rule of the characteristic parameters of gully structure with different analysis scales was analyzed by setting the scale sequence of analysis at the extraction gully. The gully structure of the watershed changed with variations in the analysis scale, and the change rule was obvious when the gully level changed. Finally, the change rule of the characteristic parameters of the gully structure at different areas was analyzed. The gully fractal dimension showed a significant numerical difference in different areas, whereas the variation of the gully branch ratio was small. The change rule indicated that the development degree of the gully obviously varied in different regions, but the morphological structure was basically similar.

Estimating nitrate emissions to surface water at regional and national scale: comparison of models using detailed regional and national-wide databases (France)

NASA Astrophysics Data System (ADS)

Dupas, R.; Gascuel-Odoux, C.; Durand, P.; Parnaudeau, V.

2012-04-01

The European Union (EU) Water Framework Directive (WFD) requires River Basin District managers to carry out an analysis of nutrient pressures and impacts, in order to evaluate the risk of water bodies failing to reach "good ecological status" and to identify those catchments where prioritized nonpoint-source control measures should be implemented. A model has been developed to estimate nitrate nonpoint-source emissions to surface water, using readily available data in France. It was inspired from US model SPARROW (Smith al., 1997) and European model GREEN (Grizzetti et al., 2008), i.e. statistical approaches consisting of linking nitrogen sources and catchments' land and rivers characteristics. The N-nitrate load (L) at the outlet of a catchment is expressed as: L= R*(B*Lsgw+Ldgw+PS)-denitlake Where denitlake is a denitrification factor for lakes and reservoirs, Lsgw is the shallow groundwater discharge to streams (derived from the base flow index and N surplus in kgN.ha-1.yr-1), Ldgw is the deep groundwater discharge to streams (derived from total runoff, the base flow index and deep groundwater N concentration), PS is point sources from domestic and industrial origin (kgN.ha-1.yr-1) and R and B are the river system and basin reduction factor, respectively. Besides calibrating and evaluating the model at a national scale, its predictive quality was compared with those of regionalized models in Brittany (Western France) and in the Seine river basin (Paris basin), where detailed regional databases are available. The national-scale model proved to provide robust predictions in most conditions encountered in France, as it fitted observed N-nitrate load with an efficiency of 0.69. Regionalization of the model reduced the standard error in the prediction of N-nitrate loads by about 19 Hence, the development of regionalized models should be advocated only after the trade-off between improvement of fit and degradation of parameters' estimation has come under scrutiny.

Evaluation of a High-Resolution Regional Reanalysis for Europe

NASA Astrophysics Data System (ADS)

Ohlwein, C.; Wahl, S.; Keller, J. D.; Bollmeyer, C.

2014-12-01

Reanalyses gain more and more importance as a source of meteorological information for many purposes and applications. Several global reanalyses projects (e.g., ERA, MERRA, CSFR, JMA9) produce and verify these data sets to provide time series as long as possible combined with a high data quality. Due to a spatial resolution down to 50-70km and 3-hourly temporal output, they are not suitable for small scale problems (e.g., regional climate assessment, meso-scale NWP verification, input for subsequent models such as river runoff simulations). The implementation of regional reanalyses based on a limited area model along with a data assimilation scheme is able to generate reanalysis data sets with high spatio-temporal resolution. Within the Hans-Ertel-Centre for Weather Research (HErZ), the climate monitoring branch concentrates efforts on the assessment and analysis of regional climate in Germany and Europe. In joint cooperation with DWD (German Meteorological Service), a high-resolution reanalysis system based on the COSMO model has been developed. The regional reanalysis for Europe matches the domain of the CORDEX EURO-11 specifications, albeit at a higher spatial resolution, i.e., 0.055° (6km) instead of 0.11° (12km) and comprises the assimilation of observational data using the existing nudging scheme of COSMO complemented by a special soil moisture analysis with boundary conditions provided by ERA-Interim data. The reanalysis data set covers 6 years (2007-2012) and is currently extended to 16 years. Extensive evaluation of the reanalysis is performed using independent observations with special emphasis on precipitation and high-impact weather situations indicating a better representation of small scale variability. Further, the evaluation shows an added value of the regional reanalysis with respect to the forcing ERA Interim reanalysis and compared to a pure high-resolution dynamical downscaling approach without data assimilation.

Improving Quantitative Precipitation Estimation via Data Fusion of High-Resolution Ground-based Radar Network and CMORPH Satellite-based Product

NASA Astrophysics Data System (ADS)

Cifelli, R.; Chen, H.; Chandrasekar, V.; Xie, P.

2015-12-01

A large number of precipitation products at multi-scales have been developed based upon satellite, radar, and/or rain gauge observations. However, how to produce optimal rainfall estimation for a given region is still challenging due to the spatial and temporal sampling difference of different sensors. In this study, we develop a data fusion mechanism to improve regional quantitative precipitation estimation (QPE) by utilizing satellite-based CMORPH product, ground radar measurements, as well as numerical model simulations. The CMORPH global precipitation product is essentially derived based on retrievals from passive microwave measurements and infrared observations onboard satellites (Joyce et al. 2004). The fine spatial-temporal resolution of 0.05o Lat/Lon and 30-min is appropriate for regional hydrologic and climate studies. However, it is inadequate for localized hydrometeorological applications such as urban flash flood forecasting. Via fusion of the Regional CMORPH product and local precipitation sensors, the high-resolution QPE performance can be improved. The area of interest is the Dallas-Fort Worth (DFW) Metroplex, which is the largest land-locked metropolitan area in the U.S. In addition to an NWS dual-polarization S-band WSR-88DP radar (i.e., KFWS radar), DFW hosts the high-resolution dual-polarization X-band radar network developed by the center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This talk will present a general framework of precipitation data fusion based on satellite and ground observations. The detailed prototype architecture of using regional rainfall instruments to improve regional CMORPH precipitation product via multi-scale fusion techniques will also be discussed. Particularly, the temporal and spatial fusion algorithms developed for the DFW Metroplex will be described, which utilizes CMORPH product, S-band WSR-88DP, and X-band CASA radar measurements. In order to investigate the uncertainties associated with each individual product and demonstrate the precipitation data fusion performance, both individual and fused QPE products are evaluated using rainfall measurements from a disdrometer and gauge network.

NASA'S SERVIR Gulf of Mexico Project: The Gulf of Mexico Regional Collaborative (GoMRC)

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Irwin, Daniel; Presson, Joan; Estes, Maury; Estes, Sue; Judd, Kathleen

2006-01-01

The Gulf of Mexico Regional Collaborative (GoMRC) is a NASA-funded project that has as its goal to develop an integrated, working, prototype IT infrastructure for Earth science data, knowledge and models for the five Gulf U.S. states and Mexico, and to demonstrate its ability to help decision-makers better understand critical Gulf-scale issues. Within this preview, the mission of this project is to provide cross cutting solution network and rapid prototyping capability for the Gulf of Mexico region, in order to demonstrate substantial, collaborative, multi-agency research and transitional capabilities using unique NASA data sets and models to address regional problems. SERVIR Mesoamerica is seen as an excellent existing framework that can be used to integrate observational and GIs data bases, provide a sensor web interface, visualization and interactive analysis tools, archival functions, data dissemination and product generation within a Rapid Prototyping concept to assist decision-makers in better understanding Gulf-scale environmental issues.

Regional Differences in Tropical Lightning Distributions.

NASA Astrophysics Data System (ADS)

Boccippio, Dennis J.; Goodman, Steven J.; Heckman, Stan

2000-12-01

Observations from the National Aeronautics and Space Administration Optical Transient Detector (OTD) and Tropical Rainfall Measuring Mission (TRMM)-based Lightning Imaging Sensor (LIS) are analyzed for variability between land and ocean, various geographic regions, and different (objectively defined) convective `regimes.' The bulk of the order-of-magnitude differences between land and ocean regional flash rates are accounted for by differences in storm spacing (density) and/or frequency of occurrence, rather than differences in storm instantaneous flash rates, which only vary by a factor of 2 on average. Regional variability in cell density and cell flash rates closely tracks differences in 85-GHz microwave brightness temperatures. Monotonic relationships are found with the gross moist stability of the tropical atmosphere, a large-scale `adjusted state' parameter. This result strongly suggests that it will be possible, using TRMM observations, to objectively test numerical or theoretical predictions of how mesoscale convective organization interacts with the larger-scale environment. Further parameters are suggested for a complete objective definition of tropical convective regimes.

Large-scale patterns formed by solar active regions during the ascending phase of cycle 21

NASA Astrophysics Data System (ADS)

Gaizauskas, V.; Harvey, K. L.; Harvey, J. W.; Zwaan, C.

1983-02-01

Synoptic maps of photospheric magnetic fields prepared at the Kitt Peak National Observatory are used in investigating large-scale patterns in the spatial and temporal distribution of solar active regions for 27 solar rotations between 1977 and 1979. The active regions are found to be distributed in 'complexes of activity' (Bumba and Howard, 1965). With the working definition of a complex of activity based on continuity and proximity of the constituent active regions, the phenomenology of complexes is explored. It is found that complexes of activity form within one month and that they are typically maintained for 3 to 6 solar rotations by fresh injections of magnetic flux. During the active lifetime of a complex of activity, the total magnetic flux in the complex remains steady to within a factor of 2. The magnetic polarities are closely balanced, and each complex rotates about the sun at its own special, constant rate. In certain cases, the complexes form two diverging branches.

Regional groundwater flow model for C, K. L. and P reactor areas, Savannah River Site, Aiken, SC

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

Flach, G.P.

2000-02-11

A regional groundwater flow model encompassing approximately 100 mi2 surrounding the C, K, L, and P reactor areas has been developed. The reactor flow model is designed to meet the planning objectives outlined in the General Groundwater Strategy for Reactor Area Projects by providing a common framework for analyzing groundwater flow, contaminant migration and remedial alternatives within the Reactor Projects team of the Environmental Restoration Department. The model provides a quantitative understanding of groundwater flow on a regional scale within the near surface aquifers and deeper semi-confined to confined aquifers. The model incorporates historical and current field characterization data upmore » through Spring 1999. Model preprocessing is automated so that future updates and modifications can be performed quickly and efficiently. The CKLP regional reactor model can be used to guide characterization, perform scoping analyses of contaminant transport, and serve as a common base for subsequent finer-scale transport and remedial/feasibility models for each reactor area.« less

Weak climatic control of stand-scale fire history during the late holocene.

PubMed

Gavin, Daniel G; Hu, Feng Sheng; Lertzman, Kenneth; Corbett, Peter

2006-07-01

Forest fire occurrence is affected by multiple controls that operate at local to regional scales. At the spatial scale of forest stands, regional climatic controls may be obscured by local controls (e.g., stochastic ignitions, topography, and fuel loads), but the long-term role of such local controls is poorly understood. We report here stand-scale (<100 ha) fire histories of the past 5000 years based on the analysis of sediment charcoal at two lakes 11 km apart in southeastern British Columbia. The two lakes are today located in similar subalpine forests, and they likely have experienced the same late-Holocene climatic changes because of their close proximity. We evaluated two independent properties of fire history: (1) fire-interval distribution, a measure of the overall incidence of fire, and (2) fire synchroneity, a measure of the co-occurrence of fire (here, assessed at centennial to millennial time scales due to the resolution of sediment records). Fire-interval distributions differed between the sites prior to, but not after, 2500 yr before present. When the entire 5000-yr period is considered, no statistical synchrony between fire-episode dates existed between the two sites at any temporal scale, but for the last 2500 yr marginal levels of synchrony occurred at centennial scales. Each individual fire record exhibited little coherency with regional climate changes. In contrast, variations in the composite record (average of both sites) matched variations in climate evidenced by late-Holocene glacial advances. This was probably due to the increased sample size and spatial extent represented by the composite record (up to 200 ha) plus increased regional climatic variability over the last several millennia, which may have partially overridden local, non-climatic controls. We conclude that (1) over past millennia, neighboring stands with similar modern conditions may have experienced different fire intervals and asynchronous patterns in fire episodes, likely because local controls outweighed the synchronizing effect of climate; (2) the influence of climate on fire occurrence is more strongly expressed when climatic variability is relatively great; and (3) multiple records from a region are essential if climate-fire relations are to be reliably described.

Uncertainty evaluation of a regional real-time system for rain-induced landslides

NASA Astrophysics Data System (ADS)

Kirschbaum, Dalia; Stanley, Thomas; Yatheendradas, Soni

2015-04-01

A new prototype regional model and evaluation framework has been developed over Central America and the Caribbean region using satellite-based information including precipitation estimates, modeled soil moisture, topography, soils, as well as regionally available datasets such as road networks and distance to fault zones. The algorithm framework incorporates three static variables: a susceptibility map; a 24-hr rainfall triggering threshold; and an antecedent soil moisture variable threshold, which have been calibrated using historic landslide events. The thresholds are regionally heterogeneous and are based on the percentile distribution of the rainfall or antecedent moisture time series. A simple decision tree algorithm framework integrates all three variables with the rainfall and soil moisture time series and generates a landslide nowcast in real-time based on the previous 24 hours over this region. This system has been evaluated using several available landslide inventories over the Central America and Caribbean region. Spatiotemporal uncertainty and evaluation metrics of the model are presented here based on available landslides reports. This work also presents a probabilistic representation of potential landslide activity over the region which can be used to further refine and improve the real-time landslide hazard assessment system as well as better identify and characterize the uncertainties inherent in this type of regional approach. The landslide algorithm provides a flexible framework to improve hazard estimation and reduce uncertainty at any spatial and temporal scale.

Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

NASA Astrophysics Data System (ADS)

Mortensen, Eric; Wu, Shu; Notaro, Michael; Vavrus, Stephen; Montgomery, Rob; De Piérola, José; Sánchez, Carlos; Block, Paul

2018-01-01

Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semiarid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Meteorological droughts in this region are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region's hydrologic cycle. An extensive season-ahead precipitation prediction model is developed to help bolster the existing capacity of stakeholders to plan for and mitigate deleterious impacts of drought. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to 11 potential predictors to produce an ensemble forecast of regional January-March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. The information provided by the developed model and ancillary modeling efforts, such as extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet-dry days per rainy season, may further assist regional stakeholders and policymakers in preparing for drought.

Impact of lateral boundary conditions on regional analyses

NASA Astrophysics Data System (ADS)

Chikhar, Kamel; Gauthier, Pierre

2017-04-01

Regional and global climate models are usually validated by comparison to derived observations or reanalyses. Using a model in data assimilation results in a direct comparison to observations to produce its own analyses that may reveal systematic errors. In this study, regional analyses over North America are produced based on the fifth-generation Canadian Regional Climate Model (CRCM5) combined with the variational data assimilation system of the Meteorological Service of Canada (MSC). CRCM5 is driven at its boundaries by global analyses from ERA-interim or produced with the global configuration of the CRCM5. Assimilation cycles for the months of January and July 2011 revealed systematic errors in winter through large values in the mean analysis increments. This bias is attributed to the coupling of the lateral boundary conditions of the regional model with the driving data particularly over the northern boundary where a rapidly changing large scale circulation created significant cross-boundary flows. Increasing the time frequency of the lateral driving and applying a large-scale spectral nudging improved significantly the circulation through the lateral boundaries which translated in a much better agreement with observations.

CO2-MEGAPARIS: Quantification of CO2 emissions from Paris megacity and their spread out to the neightbouring Centre region. (Invited)

NASA Astrophysics Data System (ADS)

Xueref-Remy, I.

2010-12-01

Atmospheric CO2 concentration has been increasing of more than 30% since the pre-industrial era due to human activities, and is very likely involved in the recent global temperature increase [IPCC, 2007]. Although we have good estimates of the CO2 fluxes on a global basis, and have a relatively well-established system to detect the large-scale trends, regional information (10-500km) is needed if society is ever to manage or verify carbon emissions. We must improve our understanding of regional variations in the sources and sinks of CO2 because they help identify possible sequestration or emission management options. New programs are needed to improve our understanding of meso-scale carbon fluxes, and to discriminate between the anthropogenic and biospheric sources which are very strongly overlapped in European countries. In this context we need to monitor the emissions originating from the megalopolis such as Paris and its agglomeration, and the way they are spreading in the background atmosphere. Nowadays, inventories (CITEPA, AIRPARIF) based on statistical information provide CO2 emissions from Ile de France and all others regions of France, but no independent verification based on CO2 measurements has been done yet. Atmospheric measurements coupled to a meso-scale model can be used to provide such verification, especially to detect the interannual and decadal trends which could result from regional management strategy. The CO2-MEGAPARIS project (2009-2012) objective is to develop four independent methods to verify the emission inventories, and to monitor the daily to monthly CO2 emissions from Ile de France as well as their spreading to neighbouring regions with a scale up to 2x2 km2. The first method consists in developing a synergy between a mesoscale model (CHIMERE/MM5), inventories and observations using a top-down approach based on an inversion technique to retrieve surface fluxes (3 new observing stations are developed among which the top of the Eiffel tower). The second method is to assess the anthropogenic emissions from Ile de France using the Radon method based on correlations between the concentrations of Radon 222 (continental tracer) and atmospheric CO2. The third method is to study the propagation of the anthropogenic plume towards the region Centre by applying an atmospheric boundary layer budget at LSCE’s observation site in Orléans forest. The fourth method is to conduct intensive measurements of in-situ CO2 and tracers (CO, potassium, dC13, dC14, ....) in Paris agglomeration to better assess the role and the variability of CO2 sources in Ile-de-France. Especially, a joined campaign with the MEGAPOLI EU-project has been conducted in winter 2010. First results of the CO2-MEGAPARIS project will be presented.

Meeting the Challenges of Regional Security

DTIC Science & Technology

1994-02-01

targets over time, assessing strike damage, and, of course, developing up-to- date maps of crucial urban and industrial areas. Coupled with modem digital ...of huge diverse data bases is key to dissecting criminal infrastructures, and identifying relevant regional and global linkages. New digital processing...cities). They can aid in reaction force planning and training. One 10-inch optical disc can easily store 25 (and display at any scale with 4- digit

Poverty assessment using DMSP/OLS night-time light satellite imagery at a provincial scale in China

NASA Astrophysics Data System (ADS)

Wang, Wen; Cheng, Hui; Zhang, Li

2012-04-01

All countries around the world and many international bodies, including the United Nations Development Program (UNDP), United Nations Food and Agricultural Organization (FAO), the International Fund for Agricultural Development (IFAD) and the International Labor Organization (ILO), have to eliminate rural poverty. Estimation of regional poverty level is a key issue for making strategies to eradicate poverty. Most of previous studies on regional poverty evaluations are based on statistics collected typically in administrative units. This paper has discussed the deficiencies of traditional studies, and attempted to research regional poverty evaluation issues using 3-year DMSP/OLS night-time light satellite imagery. In this study, we adopted 17 socio-economic indexes to establish an integrated poverty index (IPI) using principal component analysis (PCA), which was proven to provide a good descriptor of poverty levels in 31 regions at a provincial scale in China. We also explored the relationship between DMSP/OLS night-time average light index and the poverty index using regression analysis in SPSS and a good positive linear correlation was modelled, with R2 equal to 0.854. We then looked at provincial poverty problems in China based on this correlation. The research results indicated that the DMSP/OLS night-time light data can assist analysing provincial poverty evaluation issues.

Regional Air Pollutions in Three Different Regions of Asia From a Transcontinental Transport Perspective

NASA Astrophysics Data System (ADS)

Pochanart, P.; Kanaya, Y.; Komazaki, Y.; Liu, Y.; Akimoto, H.

2007-12-01

Asia is known as one of the regions with the fastest rate of growing in industrialization and urbanization. As a result, the rapid increases of large-scale air pollution in Asia emerge as a serious concern at both domestic and international levels. Apart from the problems of air quality degradation, emission control, environmental risk, and health effect in a domestic level, evidences from scientific studies indicate that by the long-range transport, Asian air pollution is becoming a global problem. Observations and model studies confirm that air pollution from Asia could be transported to North America or farther. In this work, we investigate the Asian air pollutions, in particular ozone and some other atmospheric components such as carbon monoxide and black carbon, from the ground- based observations in the three different regions, namely 1) background region of Siberia and central Asia, 2) highly anthropogenic region in eastern China, and 3) the rim region of the Asia-Pacific. In a transcontinental transport perspective, these regions are regarded as the inflow region, source region, and outflow region of Asia, respectively. From the results, it is found that the influences from large-scale emission in East Asia are observed clearly in the source region, and to the significant extent in the outflow region. For the inflow region of Asia, our data in Siberia and Kyrgyzstan indicate that air masses in this region are mostly intact from large-scale anthropogenic emission, and remain much of the global background atmospheric pollution characteristic. When the air masses are transported to source region, the air pollutants level increased sharply and frequent episodes of extremely high pollutions have been observed. Our results show good correlation between the residence time of air masses over the source region in eastern China and the observed levels of air pollutants verifying the strong enhancements by anthropogenic emissions from industrialization and urbanization. In the outflow region, air pollutants characteristics depend largely on the air mass climatology. In most cases, increases of air pollutants level are observed with the transport events directly from the source region.

Toward seamless hydrologic predictions across spatial scales

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin H.; Warrach-Sagi, Kirsten; Attinger, Sabine

2017-09-01

Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

Multiple constraint analysis of regional land-surface carbon flux

Treesearch

D.P. Turner; M. Göckede; B.E. Law; W.D. Ritts; W.B. Cohen; Z. Yang; T. Hudiburg; R. Kennedy; M. Duane

2011-01-01

We applied and compared bottom-up (process model-based) and top-down (atmospheric inversion-based) scaling approaches to evaluate the spatial and temporal patterns of net ecosystem production (NEP) over a 2.5 × 105 km2 area (the state of Oregon) in the western United States. Both approaches indicated a carbon sink over this...

River reach classification for the Greater Mekong Region at high spatial resolution

NASA Astrophysics Data System (ADS)

Ouellet Dallaire, C.; Lehner, B.

2014-12-01

River classifications have been used in river health and ecological assessments as coarse proxies to represent aquatic biodiversity when comprehensive biological and/or species data is unavailable. Currently there are no river classifications or biological data available in a consistent format for the extent of the Greater Mekong Region (GMR; including the Irrawaddy, the Salween, the Chao Praya, the Mekong and the Red River basins). The current project proposes a new river habitat classification for the region, facilitated by the HydroSHEDS (HYDROlogical SHuttle Elevation Derivatives at multiple Scales) database at 500m pixel resolution. The classification project is based on the Global River Classification framework relying on the creation of multiple sub-classifications based on different disciplines. The resulting classes from the sub-classification are later combined into final classes to create a holistic river reach classification. For the GMR, a final habitat classification was created based on three sub-classifications: a hydrological sub-classification based only on discharge indices (river size and flow variability); a physio-climatic sub-classification based on large scale indices of climate and elevation (biomes, ecoregions and elevation); and a geomorphological sub-classification based on local morphology (presence of floodplains, reach gradient and sand transport). Key variables and thresholds were identified in collaboration with local experts to ensure that regional knowledge was included. The final classification is composed 54 unique final classes based on 3 sub-classifications with less than 15 classes each. The resulting classifications are driven by abiotic variables and do not include biological data, but they represent a state-of-the art product based on best available data (mostly global data). The most common river habitat type is the "dry broadleaf, low gradient, very small river". These classifications could be applied in a wide range of hydro-ecological assessments and useful for a variety of stakeholders such as NGO, governments and researchers.

Robust skin color-based moving object detection for video surveillance

NASA Astrophysics Data System (ADS)

Kaliraj, Kalirajan; Manimaran, Sudha

2016-07-01

Robust skin color-based moving object detection for video surveillance is proposed. The objective of the proposed algorithm is to detect and track the target under complex situations. The proposed framework comprises four stages, which include preprocessing, skin color-based feature detection, feature classification, and target localization and tracking. In the preprocessing stage, the input image frame is smoothed using averaging filter and transformed into YCrCb color space. In skin color detection, skin color regions are detected using Otsu's method of global thresholding. In the feature classification, histograms of both skin and nonskin regions are constructed and the features are classified into foregrounds and backgrounds based on Bayesian skin color classifier. The foreground skin regions are localized by a connected component labeling process. Finally, the localized foreground skin regions are confirmed as a target by verifying the region properties, and nontarget regions are rejected using the Euler method. At last, the target is tracked by enclosing the bounding box around the target region in all video frames. The experiment was conducted on various publicly available data sets and the performance was evaluated with baseline methods. It evidently shows that the proposed algorithm works well against slowly varying illumination, target rotations, scaling, fast, and abrupt motion changes.

Mapping Tree Density at the Global Scale

NASA Astrophysics Data System (ADS)

Covey, K. R.; Crowther, T. W.; Glick, H.; Bettigole, C.; Bradford, M.

2015-12-01

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global-scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.39 trillion exist in tropical and subtropical regions, with 0.74, and 0.61 trillion in boreal and temperate regions, respectively. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming impact of humans across most of the world. Based on our projected tree densities, we estimate that deforestation is currently responsible for removing over 15 billion trees each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Mapping tree density at a global scale

NASA Astrophysics Data System (ADS)

Crowther, T. W.; Glick, H. B.; Covey, K. R.; Bettigole, C.; Maynard, D. S.; Thomas, S. M.; Smith, J. R.; Hintler, G.; Duguid, M. C.; Amatulli, G.; Tuanmu, M.-N.; Jetz, W.; Salas, C.; Stam, C.; Piotto, D.; Tavani, R.; Green, S.; Bruce, G.; Williams, S. J.; Wiser, S. K.; Huber, M. O.; Hengeveld, G. M.; Nabuurs, G.-J.; Tikhonova, E.; Borchardt, P.; Li, C.-F.; Powrie, L. W.; Fischer, M.; Hemp, A.; Homeier, J.; Cho, P.; Vibrans, A. C.; Umunay, P. M.; Piao, S. L.; Rowe, C. W.; Ashton, M. S.; Crane, P. R.; Bradford, M. A.

2015-09-01

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.39 trillion exist in tropical and subtropical forests, with 0.74 trillion in boreal regions and 0.61 trillion in temperate regions. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming effect of humans across most of the world. Based on our projected tree densities, we estimate that over 15 billion trees are cut down each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Mapping tree density at a global scale.

PubMed

Crowther, T W; Glick, H B; Covey, K R; Bettigole, C; Maynard, D S; Thomas, S M; Smith, J R; Hintler, G; Duguid, M C; Amatulli, G; Tuanmu, M-N; Jetz, W; Salas, C; Stam, C; Piotto, D; Tavani, R; Green, S; Bruce, G; Williams, S J; Wiser, S K; Huber, M O; Hengeveld, G M; Nabuurs, G-J; Tikhonova, E; Borchardt, P; Li, C-F; Powrie, L W; Fischer, M; Hemp, A; Homeier, J; Cho, P; Vibrans, A C; Umunay, P M; Piao, S L; Rowe, C W; Ashton, M S; Crane, P R; Bradford, M A

2015-09-10

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.39 trillion exist in tropical and subtropical forests, with 0.74 trillion in boreal regions and 0.61 trillion in temperate regions. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming effect of humans across most of the world. Based on our projected tree densities, we estimate that over 15 billion trees are cut down each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Landscape-and regional-scale shifts in forest composition under climate change in the Central Hardwood Region of the United States

Treesearch

Wen J. Wang; Hong S. He; Frank R. Thompson; Jacob S. Fraser; William D. Dijak

2016-01-01

Tree species distribution and abundance are affected by forces operating at multiple scales. Niche and biophysical process models have been commonly used to predict climate change effects at regional scales, however, these models have limited capability to include site-scale population dynamics and landscape- scale disturbance and dispersal. We applied a landscape...

Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States

EPA Science Inventory

This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boun...

Prospective and participatory integrated assessment of agricultural systems from farm to regional scales: Comparison of three modeling approaches.

PubMed

Delmotte, Sylvestre; Lopez-Ridaura, Santiago; Barbier, Jean-Marc; Wery, Jacques

2013-11-15

Evaluating the impacts of the development of alternative agricultural systems, such as organic or low-input cropping systems, in the context of an agricultural region requires the use of specific tools and methodologies. They should allow a prospective (using scenarios), multi-scale (taking into account the field, farm and regional level), integrated (notably multicriteria) and participatory assessment, abbreviated PIAAS (for Participatory Integrated Assessment of Agricultural System). In this paper, we compare the possible contribution to PIAAS of three modeling approaches i.e. Bio-Economic Modeling (BEM), Agent-Based Modeling (ABM) and statistical Land-Use/Land Cover Change (LUCC) models. After a presentation of each approach, we analyze their advantages and drawbacks, and identify their possible complementarities for PIAAS. Statistical LUCC modeling is a suitable approach for multi-scale analysis of past changes and can be used to start discussion about the futures with stakeholders. BEM and ABM approaches have complementary features for scenarios assessment at different scales. While ABM has been widely used for participatory assessment, BEM has been rarely used satisfactorily in a participatory manner. On the basis of these results, we propose to combine these three approaches in a framework targeted to PIAAS. Copyright © 2013 Elsevier Ltd. All rights reserved.

Linking Domain-Specific Models to Describe the Complex Dynamics and Management Options of a Saline Floodplain

NASA Astrophysics Data System (ADS)

Woods, J.; Laattoe, T.

2016-12-01

Complex hydrological environments present management challenges where surface water-groundwater interactions involve interlinked processes at multiple scales. One example is Australia's River Murray, which flows through a semi-arid landscape with highly saline groundwater. In this region, the floodplain ecology depends on freshwater provided from the main river channel, anabranches, and floodwaters. However, in the past century access to freshwater has been further limited due to river regulation, land clearance, and irrigation. A programme to improve ecosystem health at Pike Floodplain, South Australia, is evaluating management options such as environmental watering and groundwater pumping. Due to the complicated interdependencies between processes moving water and salt within the floodplain, a series of inter-linked models were developed to assist with management decisions. The models differ by hydrological domain, scale, and dimensionality. Together they simulate surface water, the unsaturated zone, and groundwater on regional, floodplain, and local scales. Outputs from regional models provide boundary conditions for floodplain models, which in turn provide inputs for the local scale models. The results are interpreted based on (i) ecohydrological requirements for key species of tree and fish, and (ii) impacts on river salinity for downstream users. When combined, the models provide an integrated and interdiscplinary understanding of the hydrology and management of saline floodplains.

Estimation of regional-scale groundwater flow properties in the Bengal Basin of India and Bangladesh

USGS Publications Warehouse

Michael, H.A.; Voss, C.I.

2009-01-01

Quantitative evaluation of management strategies for long-term supply of safe groundwater for drinking from the Bengal Basin aquifer (India and Bangladesh) requires estimation of the large-scale hydrogeologic properties that control flow. The Basin consists of a stratified, heterogeneous sequence of sediments with aquitards that may separate aquifers locally, but evidence does not support existence of regional confining units. Considered at a large scale, the Basin may be aptly described as a single aquifer with higher horizontal than vertical hydraulic conductivity. Though data are sparse, estimation of regional-scale aquifer properties is possible from three existing data types: hydraulic heads, 14C concentrations, and driller logs. Estimation is carried out with inverse groundwater modeling using measured heads, by model calibration using estimated water ages based on 14C, and by statistical analysis of driller logs. Similar estimates of hydraulic conductivities result from all three data types; a resulting typical value of vertical anisotropy (ratio of horizontal to vertical conductivity) is 104. The vertical anisotropy estimate is supported by simulation of flow through geostatistical fields consistent with driller log data. The high estimated value of vertical anisotropy in hydraulic conductivity indicates that even disconnected aquitards, if numerous, can strongly control the equivalent hydraulic parameters of an aquifer system. ?? US Government 2009.

The Transition Region Explorer: Observing the Multi-Scale Dynamics of Geospace

NASA Astrophysics Data System (ADS)

Donovan, E.

2015-12-01

Meso- and global-scale IT remote sensing is accomplished via satellite imagers and ground-based instruments. On the ground, the approach is arrays providing extensive as possible coverage (the "net") and powerful observatories that drill deep to provide detailed information about small-scale processes (the "drill"). Always, there is a trade between cost, spatial resolution, coverage (extent), number of parameters, and more, such that in general the larger the network the sparser the coverage. Where are we now? There are important gaps. With THEMIS-ASI, we see processes that quickly evolve beyond the field of view of one observatory, but involve space/time scales not captured by existing meso- and large-scale arrays. Many forefront questions require observations at heretofore unexplored space and time scales, and comprehensive inter-hemispheric conjugate observations than are presently available. To address this, a new ground-based observing initiative is being developed in Canada. Called TREx, for Transition Region Explorer, this new facility will incorporate dedicated blueline, redline, and Near-Infrared All-Sky Imagers, together with an unprecedented network of ten imaging riometers, with a combined field of view spanning more than three hours of magnetic local time and from equatorward to poleward of typical auroral latitudes (spanning the ionospheric footprint of the "nightside transition region" that separates the highly stretched tail and the inner magnetosphere). The TREx field-of-view is covered by HF radars, and contains a dense network of magnetometers and VLF receivers, as well as other geospace and upper atmospheric remote sensors. Taken together, TREx and these co-located instruments represent a quantum leap forward in terms of imaging, in multiple parameters (precipitation, ionization, convection, and currents), ionospheric dynamics in the above-mentioned scale gap. This represents an exciting new opportunity for studying geospace at the system level, especially for using the aurora to remote sense magnetospheric plasma physics and dynamics, and comes with a set of Big Data challenges that are going to be exciting. One such challenge is the development of a fundamentally new type of data product, namely time series of multi-parameter, geospatially referenced 'data cubes'.

Lack of sex-biased dispersal promotes fine-scale genetic structure in alpine ungulates

USGS Publications Warehouse

Roffler, Gretchen H.; Talbot, Sandra L.; Luikart, Gordon; Sage, George K.; Pilgrim, Kristy L.; Adams, Layne G.; Schwartz, Michael K.

2014-01-01

Identifying patterns of fine-scale genetic structure in natural populations can advance understanding of critical ecological processes such as dispersal and gene flow across heterogeneous landscapes. Alpine ungulates generally exhibit high levels of genetic structure due to female philopatry and patchy configuration of mountain habitats. We assessed the spatial scale of genetic structure and the amount of gene flow in 301 Dall’s sheep (Ovis dalli dalli) at the landscape level using 15 nuclear microsatellites and 473 base pairs of the mitochondrial (mtDNA) control region. Dall’s sheep exhibited significant genetic structure within contiguous mountain ranges, but mtDNA structure occurred at a broader geographic scale than nuclear DNA within the study area, and mtDNA structure for other North American mountain sheep populations. No evidence of male-mediated gene flow or greater philopatry of females was observed; there was little difference between markers with different modes of inheritance (pairwise nuclear DNA F ST = 0.004–0.325; mtDNA F ST = 0.009–0.544), and males were no more likely than females to be recent immigrants. Historical patterns based on mtDNA indicate separate northern and southern lineages and a pattern of expansion following regional glacial retreat. Boundaries of genetic clusters aligned geographically with prominent mountain ranges, icefields, and major river valleys based on Bayesian and hierarchical modeling of microsatellite and mtDNA data. Our results suggest that fine-scale genetic structure in Dall’s sheep is influenced by limited dispersal, and structure may be weaker in populations occurring near ancestral levels of density and distribution in continuous habitats compared to other alpine ungulates that have experienced declines and marked habitat fragmentation.

Biodiversity Mapping via Natura 2000 Conservation Status and Ebv Assessment Using Airborne Laser Scanning in Alkali Grasslands

NASA Astrophysics Data System (ADS)

Zlinszky, A.; Deák, B.; Kania, A.; Schroiff, A.; Pfeifer, N.

2016-06-01

Biodiversity is an ecological concept, which essentially involves a complex sum of several indicators. One widely accepted such set of indicators is prescribed for habitat conservation status assessment within Natura 2000, a continental-scale conservation programme of the European Union. Essential Biodiversity Variables are a set of indicators designed to be relevant for biodiversity and suitable for global-scale operational monitoring. Here we revisit a study of Natura 2000 conservation status mapping via airbone LIDAR that develops individual remote sensing-derived proxies for every parameter required by the Natura 2000 manual, from the perspective of developing regional-scale Essential Biodiversity Variables. Based on leaf-on and leaf-off point clouds (10 pt/m2) collected in an alkali grassland area, a set of data products were calculated at 0.5 ×0.5 m resolution. These represent various aspects of radiometric and geometric texture. A Random Forest machine learning classifier was developed to create fuzzy vegetation maps of classes of interest based on these data products. In the next step, either classification results or LIDAR data products were selected as proxies for individual Natura 2000 conservation status variables, and fine-tuned based on field references. These proxies showed adequate performance and were summarized to deliver Natura 2000 conservation status with 80% overall accuracy compared to field references. This study draws attention to the potential of LIDAR for regional-scale Essential Biodiversity variables, and also holds implications for global-scale mapping. These are (i) the use of sensor data products together with habitat-level classification, (ii) the utility of seasonal data, including for non-seasonal variables such as grassland canopy structure, and (iii) the potential of fuzzy mapping-derived class probabilities as proxies for species presence and absence.

Application of an improved spectral decomposition method to examine earthquake source scaling in Southern California

NASA Astrophysics Data System (ADS)

Trugman, Daniel T.; Shearer, Peter M.

2017-04-01

Earthquake source spectra contain fundamental information about the dynamics of earthquake rupture. However, the inherent tradeoffs in separating source and path effects, when combined with limitations in recorded signal bandwidth, make it challenging to obtain reliable source spectral estimates for large earthquake data sets. We present here a stable and statistically robust spectral decomposition method that iteratively partitions the observed waveform spectra into source, receiver, and path terms. Unlike previous methods of its kind, our new approach provides formal uncertainty estimates and does not assume self-similar scaling in earthquake source properties. Its computational efficiency allows us to examine large data sets (tens of thousands of earthquakes) that would be impractical to analyze using standard empirical Green's function-based approaches. We apply the spectral decomposition technique to P wave spectra from five areas of active contemporary seismicity in Southern California: the Yuha Desert, the San Jacinto Fault, and the Big Bear, Landers, and Hector Mine regions of the Mojave Desert. We show that the source spectra are generally consistent with an increase in median Brune-type stress drop with seismic moment but that this observed deviation from self-similar scaling is both model dependent and varies in strength from region to region. We also present evidence for significant variations in median stress drop and stress drop variability on regional and local length scales. These results both contribute to our current understanding of earthquake source physics and have practical implications for the next generation of ground motion prediction assessments.

Agroforestry-based management of salt-affected croplands in irrigated agricultural landscape in Uzbekistan

NASA Astrophysics Data System (ADS)

Khamzina, Asia; Kumar, Navneet; Heng, Lee

2017-04-01

In the lower Amu Darya River Basin, the decades of intensive irrigation led to elevated groundwater tables, resulting in ubiquitous soil salinization and adverse impact on crop production. Field-scale afforestation trials and farm-scale economic analyses in the Khorezm region have determined that afforestation can be an environmentally and financially attractive land-use option for degraded croplands because it combines a diversified agricultural production, carbon sequestration, an improved soil health and minimizes the use of irrigation water. We examined prospects for upscaling afforestation activity for regional land-use planning considering prevailing constraints in irrigated agriculture landscape. Assessment of salinity-induced cropland productivity decline using satellite imagery of multiple spatial and temporal resolution revealed that 18-38% of the marginally productive or abandoned cropland might be considered for conversion to agroforestry. Furthermore, a regional-scale water balance suggests that most of these marginal croplands are characterized by sufficient surface water supplies for irrigating the newly planted saplings, before they are able to rely on the groundwater alone. However, the 10-year monitoring of soil salt dynamics in the afforestation trials reveals increasing salinity levels due to the salt exclusion from the root water uptake by the trees. Further study focuses on enhancing long-term sustainability of afforestation as a management option for highly saline lands by examining salt tolerance of candidate species using 13C isotopic signature as the indicator of water and salt stress, salt leaching needs and implications for regional scale planning.

Quantitative Assessment of Desertification Using Landsat Data on a Regional Scale – A Case Study in the Ordos Plateau, China

PubMed Central

Xu, Duanyang; Kang, Xiangwu; Qiu, Dongsheng; Zhuang, Dafang; Pan, Jianjun

2009-01-01

Desertification is a serious threat to the ecological environment and social economy in our world and there is a pressing need to develop a reasonable and reproducible method to assess it at different scales. In this paper, the Ordos Plateau in China was selected as the research region and a quantitative method for desertification assessment was developed by using Landsat MSS and TM/ETM+ data on a regional scale. In this method, NDVI, MSDI and land surface albedo were selected as assessment indicators of desertification to represent land surface conditions from vegetation biomass, landscape pattern and micrometeorology. Based on considering the effects of vegetation type and time of images acquired on assessment indictors, assessing rule sets were built and a decision tree approach was used to assess desertification of Ordos Plateau in 1980, 1990 and 2000. The average overall accuracy of three periods was higher than 90%. The results showed that although some local places of Ordos Plateau experienced an expanding trend of desertification, the trend of desertification of Ordos Plateau was an overall decrease in from 1980 to 2000. By analyzing the causes of desertification processes, it was found that climate change could benefit for the reversion of desertification from 1980 to 1990 at a regional scale and human activities might explain the expansion of desertification in this period; however human conservation activities were the main driving factor that induced the reversion of desertification from 1990 to 2000. PMID:22573984

Effects of increased wind power generation on Mid-Norway's energy balance under climate change: A market based approach

NASA Astrophysics Data System (ADS)

Francois, Baptiste; Martino, Sara; Tofte, Lena; Hingray, Benoit; Mo, Birger; Creutin, Jean-Dominique

2017-04-01

Thanks to its huge water storage capacity, Norway has an excess of energy generation at annual scale, although significant regional disparity exists. On average, the Mid-Norway region has an energy deficit and needs to import more electricity than it exports. We show that this energy deficit can be reduced with an increase in wind generation and transmission line capacity, even in future climate scenarios where both mean annual temperature and precipitation are changed. For the considered scenarios, the deficit observed in winter disappears, i.e. when electricity consumption and prices are high. At the annual scale, the deficit behavior depends more on future changes in precipitation. Another consequence of changes in wind production and transmission capacity is the modification of electricity exchanges with neighboring regions which are also modified both in terms of average, variability and seasonality. Keywords: Variable renewable energy, Wind, Hydro, Energy balance, Energy market

Observational evidence for cloud cover enhancement over western European forests.

PubMed

Teuling, Adriaan J; Taylor, Christopher M; Meirink, Jan Fokke; Melsen, Lieke A; Miralles, Diego G; van Heerwaarden, Chiel C; Vautard, Robert; Stegehuis, Annemiek I; Nabuurs, Gert-Jan; de Arellano, Jordi Vilà-Guerau

2017-01-11

Forests impact regional hydrology and climate directly by regulating water and heat fluxes. Indirect effects through cloud formation and precipitation can be important in facilitating continental-scale moisture recycling but are poorly understood at regional scales. In particular, the impact of temperate forest on clouds is largely unknown. Here we provide observational evidence for a strong increase in cloud cover over large forest regions in western Europe based on analysis of 10 years of 15 min resolution data from geostationary satellites. In addition, we show that widespread windthrow by cyclone Klaus in the Landes forest led to a significant decrease in local cloud cover in subsequent years. Strong cloud development along the downwind edges of larger forest areas are consistent with a forest-breeze mesoscale circulation. Our results highlight the need to include impacts on cloud formation when evaluating the water and climate services of temperate forests, in particular around densely populated areas.

Observational evidence for cloud cover enhancement over western European forests

PubMed Central

Teuling, Adriaan J.; Taylor, Christopher M.; Meirink, Jan Fokke; Melsen, Lieke A.; Miralles, Diego G.; van Heerwaarden, Chiel C.; Vautard, Robert; Stegehuis, Annemiek I.; Nabuurs, Gert-Jan; de Arellano, Jordi Vilà-Guerau

2017-01-01

Forests impact regional hydrology and climate directly by regulating water and heat fluxes. Indirect effects through cloud formation and precipitation can be important in facilitating continental-scale moisture recycling but are poorly understood at regional scales. In particular, the impact of temperate forest on clouds is largely unknown. Here we provide observational evidence for a strong increase in cloud cover over large forest regions in western Europe based on analysis of 10 years of 15 min resolution data from geostationary satellites. In addition, we show that widespread windthrow by cyclone Klaus in the Landes forest led to a significant decrease in local cloud cover in subsequent years. Strong cloud development along the downwind edges of larger forest areas are consistent with a forest-breeze mesoscale circulation. Our results highlight the need to include impacts on cloud formation when evaluating the water and climate services of temperate forests, in particular around densely populated areas. PMID:28074840

The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

NASA Astrophysics Data System (ADS)

Chuan, Zun Liang; Ismail, Noriszura; Shinyie, Wendy Ling; Lit Ken, Tan; Fam, Soo-Fen; Senawi, Azlyna; Yusoff, Wan Nur Syahidah Wan

2018-04-01

Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.

Communication between Brain Areas Based on Nested Oscillations

PubMed Central

Kastner, Sabine

2017-01-01

Abstract Unraveling how brain regions communicate is crucial for understanding how the brain processes external and internal information. Neuronal oscillations within and across brain regions have been proposed to play a crucial role in this process. Two main hypotheses have been suggested for routing of information based on oscillations, namely communication through coherence and gating by inhibition. Here, we propose a framework unifying these two hypotheses that is based on recent empirical findings. We discuss a theory in which communication between two regions is established by phase synchronization of oscillations at lower frequencies (<25 Hz), which serve as temporal reference frame for information carried by high-frequency activity (>40 Hz). Our framework, consistent with numerous recent empirical findings, posits that cross-frequency interactions are essential for understanding how large-scale cognitive and perceptual networks operate. PMID:28374013

Coral Mortality and Bleaching Output

EPA Science Inventory

COMBO is a spreadsheet-based model for the use of managers, conservationists, and biologists for projecting the effects of climate change on coral reefs at local-to-regional scales. The COMBO (Coral Mortality and Bleaching Output) model calculates the impacts to coral reefs from...

Neurodevelopmental alterations of large-scale structural networks in children with new-onset epilepsy

PubMed Central

Bonilha, Leonardo; Tabesh, Ali; Dabbs, Kevin; Hsu, David A.; Stafstrom, Carl E.; Hermann, Bruce P.; Lin, Jack J.

2014-01-01

Recent neuroimaging and behavioral studies have revealed that children with new onset epilepsy already exhibit brain structural abnormalities and cognitive impairment. How the organization of large-scale brain structural networks is altered near the time of seizure onset and whether network changes are related to cognitive performances remain unclear. Recent studies also suggest that regional brain volume covariance reflects synchronized brain developmental changes. Here, we test the hypothesis that epilepsy during early-life is associated with abnormalities in brain network organization and cognition. We used graph theory to study structural brain networks based on regional volume covariance in 39 children with new-onset seizures and 28 healthy controls. Children with new-onset epilepsy showed a suboptimal topological structural organization with enhanced network segregation and reduced global integration compared to controls. At the regional level, structural reorganization was evident with redistributed nodes from the posterior to more anterior head regions. The epileptic brain network was more vulnerable to targeted but not random attacks. Finally, a subgroup of children with epilepsy, namely those with lower IQ and poorer executive function, had a reduced balance between network segregation and integration. Taken together, the findings suggest that the neurodevelopmental impact of new onset childhood epilepsies alters large-scale brain networks, resulting in greater vulnerability to network failure and cognitive impairment. PMID:24453089

Coronal mass ejections and their sheath regions in interplanetary space

NASA Astrophysics Data System (ADS)

Kilpua, Emilia; Koskinen, Hannu E. J.; Pulkkinen, Tuija I.

2017-11-01

Interplanetary coronal mass ejections (ICMEs) are large-scale heliospheric transients that originate from the Sun. When an ICME is sufficiently faster than the preceding solar wind, a shock wave develops ahead of the ICME. The turbulent region between the shock and the ICME is called the sheath region. ICMEs and their sheaths and shocks are all interesting structures from the fundamental plasma physics viewpoint. They are also key drivers of space weather disturbances in the heliosphere and planetary environments. ICME-driven shock waves can accelerate charged particles to high energies. Sheaths and ICMEs drive practically all intense geospace storms at the Earth, and they can also affect dramatically the planetary radiation environments and atmospheres. This review focuses on the current understanding of observational signatures and properties of ICMEs and the associated sheath regions based on five decades of studies. In addition, we discuss modelling of ICMEs and many fundamental outstanding questions on their origin, evolution and effects, largely due to the limitations of single spacecraft observations of these macro-scale structures. We also present current understanding of space weather consequences of these large-scale solar wind structures, including effects at the other Solar System planets and exoplanets. We specially emphasize the different origin, properties and consequences of the sheaths and ICMEs.

Satellite Based Analysis of Wood Biomass and Fuelwood Sustainability in Senegal: Developing Approaches for Long-Term Monitoring in the SERVIR-West Africa Region

NASA Astrophysics Data System (ADS)

Hanan, N. P.; Anchang, J.; Dieye, A. M.; Yero, K.; Tredennick, A. T.

2017-12-01

Rural populations in most of Africa are highly dependent on woody biomass (wood or charcoal) for cooking and heating. Many rural families gather wood locally, while urban populations often rely on small-scale commercial charcoal producers, who make charcoal in rural areas for transport to urban centers. Given that cooking is essential for conversion of inedible protein and carbohydrate substrates into edible food, fuelwood is an essential part of the food security puzzle for most African families. The SERVIR program is a partnership between USAID, NASA and regional institutions designed to enhance access to, and application of, earth observation data for economic development and natural resource management in less developed countries. In this paper, we report on a SERVIR West Africa collaboration to develop above-ground wood biomass estimates using moderate resolution ( 20 m) data from Sentinel-1 and Sentinel-2 satellites, incorporating field data for calibration and validation, and using data retrieval and analysis workflows that can be replicated by SERVIR partners across the region. Using the country of Senegal as a test case, we analyze the spatial distribution of biomass stocks in relation to fuelwood demand to assess supply-demand patterns across scales from local (village), to district, regional and national scales.

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

2017-01-01

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

What's Happening on the West Coast? The National Ocean Policy, EBM and Ocean Governance on the West Coast of the U.S.

NASA Astrophysics Data System (ADS)

Hansen, J. R.

2016-02-01

A robust update on the latest ocean governance developments in the West Coast region of the U.S. will be provided, highlighting implementation of the National Ocean Policy and ongoing dialog among federal, state and tribal entities and coastal stakeholders at a range of scales. The link between ecosystem-based management (EBM) as a guiding principle and meaningful management outcomes will discussed, guided by the latest ocean policy priorities from local, state, tribal and regional scales in the West Coast. The West Coast Regional Planning Body has been recently initiated under the framework provided by the National Ocean Policy, bringing together a formal partnership of state and tribal governments with federal agencies in a way never before achieved in the region. The newly reformed West Coast Ocean Partnership builds upon efforts of the West Coast Governors Alliance on Ocean Health to continue to address priority ocean policy topics, while other regional efforts are identifying data, science and tools to support an EBM approach. All of these will be discussed in detail, providing both up-to-date reports on the latest West Coast activities, while illustrating lessons learned from past regional efforts and exactly how EBM has been effectively integrated. The West Coast of the U.S. is a unique region in terms of geographic scale, governance structure and history of innovative ocean management approaches. Using opportunities provided by recent state, tribal, regional and national policy initiatives, the West Coast has undertaken a range of activities to better coordinate ocean management while enhancing dialogs to support it. This presentation will provide a concise summary of current efforts, demonstrating how policy is being translated into significant action and highlighting opportunities to build on successful outcomes to date.

What's Happening on the West Coast? The National Ocean Policy, EBM and Ocean Governance on the West Coast of the U.S.

NASA Astrophysics Data System (ADS)

Hansen, J. R.

2016-12-01

A robust update on the latest ocean governance developments in the West Coast region of the U.S. will be provided, highlighting implementation of the National Ocean Policy and ongoing dialog among federal, state and tribal entities and coastal stakeholders at a range of scales. The link between ecosystem-based management (EBM) as a guiding principle and meaningful management outcomes will discussed, guided by the latest ocean policy priorities from local, state, tribal and regional scales in the West Coast. The West Coast Regional Planning Body has been recently initiated under the framework provided by the National Ocean Policy, bringing together a formal partnership of state and tribal governments with federal agencies in a way never before achieved in the region. The newly reformed West Coast Ocean Partnership builds upon efforts of the West Coast Governors Alliance on Ocean Health to continue to address priority ocean policy topics, while other regional efforts are identifying data, science and tools to support an EBM approach. All of these will be discussed in detail, providing both up-to-date reports on the latest West Coast activities, while illustrating lessons learned from past regional efforts and exactly how EBM has been effectively integrated. The West Coast of the U.S. is a unique region in terms of geographic scale, governance structure and history of innovative ocean management approaches. Using opportunities provided by recent state, tribal, regional and national policy initiatives, the West Coast has undertaken a range of activities to better coordinate ocean management while enhancing dialogs to support it. This presentation will provide a concise summary of current efforts, demonstrating how policy is being translated into significant action and highlighting opportunities to build on successful outcomes to date.

Functional connectivity in the resting brain as biological correlate of the Affective Neuroscience Personality Scales.

PubMed

Deris, Nadja; Montag, Christian; Reuter, Martin; Weber, Bernd; Markett, Sebastian

2017-02-15

According to Jaak Panksepp's Affective Neuroscience Theory and the derived self-report measure, the Affective Neuroscience Personality Scales (ANPS), differences in the responsiveness of primary emotional systems form the basis of human personality. In order to investigate neuronal correlates of personality, the underlying neuronal circuits of the primary emotional systems were analyzed in the present fMRI-study by associating the ANPS to functional connectivity in the resting brain. N=120 healthy participants were invited for the present study. The results were reinvestigated in an independent, smaller sample of N=52 participants. A seed-based whole brain approach was conducted with seed-regions bilaterally in the basolateral and superficial amygdalae. The selection of seed-regions was based on meta-analytic data on affective processing and the Juelich histological atlas. Multiple regression analyses on the functional connectivity maps revealed associations with the SADNESS-scale in both samples. Functional resting-state connectivity between the left basolateral amygdala and a cluster in the postcentral gyrus, and between the right basolateral amygdala and clusters in the superior parietal lobe and subgyral in the parietal lobe was associated with SADNESS. No other ANPS-scale revealed replicable results. The present findings give first insights into the neuronal basis of the SADNESS-scale of the ANPS and support the idea of underlying neuronal circuits. In combination with previous research on genetic associations of the ANPS functional resting-state connectivity is discussed as a possible endophenotype of personality. Copyright © 2016 Elsevier Inc. All rights reserved.

More robust regional precipitation projection from selected CMIP5 models based on multiple-dimensional metrics

NASA Astrophysics Data System (ADS)

Qian, Y.; Wang, L.; Leung, L. R.; Lin, G.; Lu, J.; Gao, Y.; Zhang, Y.

2017-12-01

Projecting precipitation changes is challenging because of incomplete understanding of the climate system and biases and uncertainty in climate models. In East Asia where summer precipitation is dominantly influenced by the monsoon circulation and the global models from Coupled Model Intercomparison Project Phase 5 (CMIP5), however, give various projection of precipitation change for 21th century. It is critical for community to know which models' projection are more reliable in response to natural and anthropogenic forcings. In this study we defined multiple-dimensional metrics, measuring the model performance in simulating the present-day of large-scale circulation, regional precipitation and relationship between them. The large-scale circulation features examined in this study include the lower tropospheric southwesterly winds, the western North Pacific subtropical high, the South China Sea Subtropical High, and the East Asian westerly jet in the upper troposphere. Each of these circulation features transport moisture to East Asia, enhancing the moist static energy and strengthening the Meiyu moisture front that is the primary mechanism for precipitation generation in eastern China. Based on these metrics, 30 models in CMIP5 ensemble are classified into three groups. Models in the top performing group projected regional precipitation patterns that are more similar to each other than the bottom or middle performing group and consistently projected statistically significant increasing trends in two of the large-scale circulation indices and precipitation. In contrast, models in the bottom or middle performing group projected small drying or no trends in precipitation. We also find the models that only reasonably reproduce the observed precipitation climatology does not guarantee more reliable projection of future precipitation because good simulation skill could be achieved through compensating errors from multiple sources. Herein the potential for more robust projections of precipitation changes at regional scale is demonstrated through the use of discriminating metric to subsample the multi-model ensemble. The results from this study provides insights for how to select models from CMIP ensemble to project regional climate and hydrological cycle changes.

Upper mantle diapers, lower crustal magmatic underplating, and lithospheric dismemberment of the Great Basin and Colorado Plateau regions, Nevada and Utah; implications from deep MT resistivity surveying

NASA Astrophysics Data System (ADS)

Wannamaker, P. E.; Doerner, W. M.; Hasterok, D. P.

2005-12-01

In the rifted Basin and Range province of the southwestern U.S., a common faulting model for extensional basins based e.g. on reflection seismology data shows dominant displacement along master faults roughly coincident with the main topographic scarp. On the other hand, complementary data such as drilling, earthquake focal mechanisms, volcanic occurrences, and trace indicators such as helium isotopes suggest that there are alternative geometries of crustal scale faulting and material transport from the deep crust and upper mantle in this province. Recent magnetotelluric (MT) profiling results reveal families of structures commonly dominated by high-angle conductors interpreted to reflect crustal scale fault zones. Based mainly on cross cutting relationships, these faults appear to be late Cenozoic in age and are of low resistivity due to fluids or alteration (including possible graphitization). In the Ruby Mtns area of north-central Nevada, high angle faults along the margins of the core complex connect from near surface to a regional lower crustal conductor interpreted to contain high-temperature fluids and perhaps melts. Such faults may exemplify the high angle normal faults upon which the major earthquakes of the Great Basin appear to nucleate. A larger-scale transect centered on Dixie Valley shows major conductive crustal-scale structures connecting to conductive lower crust below Dixie Valley, the Black Rock desert in NW Nevada, and in east-central Nevada in the Monitor-Diamond Valley area. In the Great Basin-Colorado Plateau transition of Utah, the main structures revealed are a series of nested low-angle detachment structures underlying the incipient development of several rift grabens. All these major fault zones appear to overlie regions of particularly conductive lower crust interpreted to be caused by recent basaltic underplating. In the GB-CP transition, long period data show two, low-resistivity upper mantle diapirs underlying the concentrated conductive lower crust and nested faults, and these are advanced as melt source regions for the underplating. MT, with its wide frequency bandwidth, allows views of nearly a complete melting and emplacement process, from mantle source region, through lower crustal intrusion, to brittle regime deformational response.

Fuzzy Matching Based on Gray-scale Difference for Quantum Images

NASA Astrophysics Data System (ADS)

Luo, GaoFeng; Zhou, Ri-Gui; Liu, XingAo; Hu, WenWen; Luo, Jia

2018-05-01

Quantum image processing has recently emerged as an essential problem in practical tasks, e.g. real-time image matching. Previous studies have shown that the superposition and entanglement of quantum can greatly improve the efficiency of complex image processing. In this paper, a fuzzy quantum image matching scheme based on gray-scale difference is proposed to find out the target region in a reference image, which is very similar to the template image. Firstly, we employ the proposed enhanced quantum representation (NEQR) to store digital images. Then some certain quantum operations are used to evaluate the gray-scale difference between two quantum images by thresholding. If all of the obtained gray-scale differences are not greater than the threshold value, it indicates a successful fuzzy matching of quantum images. Theoretical analysis and experiments show that the proposed scheme performs fuzzy matching at a low cost and also enables exponentially significant speedup via quantum parallel computation.

A simple scaling approach to produce climate scenarios of local precipitation extremes for the Netherlands

NASA Astrophysics Data System (ADS)

Lenderink, Geert; Attema, Jisk

2015-08-01

Scenarios of future changes in small scale precipitation extremes for the Netherlands are presented. These scenarios are based on a new approach whereby changes in precipitation extremes are set proportional to the change in water vapor amount near the surface as measured by the 2m dew point temperature. This simple scaling framework allows the integration of information derived from: (i) observations, (ii) a new unprecedentedly large 16 member ensemble of simulations with the regional climate model RACMO2 driven by EC-Earth, and (iii) short term integrations with a non-hydrostatic model Harmonie. Scaling constants are based on subjective weighting (expert judgement) of the three different information sources taking also into account previously published work. In all scenarios local precipitation extremes increase with warming, yet with broad uncertainty ranges expressing incomplete knowledge of how convective clouds and the atmospheric mesoscale circulation will react to climate change.

Improving Shade Modelling in a Regional River Temperature Model Using Fine-Scale LIDAR Data

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Loicq, P.; Moatar, F.; Beaufort, A.; Melin, E.; Jullian, Y.

2015-12-01

Air temperature is often considered as a proxy of the stream temperature to model the distribution areas of aquatic species water temperature is not available at a regional scale. To simulate the water temperature at a regional scale (105 km²), a physically-based model using the equilibrium temperature concept and including upstream-downstream propagation of the thermal signal was developed and applied to the entire Loire basin (Beaufort et al., submitted). This model, called T-NET (Temperature-NETwork) is based on a hydrographical network topology. Computations are made hourly on 52,000 reaches which average 1.7 km long in the Loire drainage basin. The model gives a median Root Mean Square Error of 1.8°C at hourly time step on the basis of 128 water temperature stations (2008-2012). In that version of the model, tree shadings is modelled by a constant factor proportional to the vegetation cover on 10 meters sides the river reaches. According to sensitivity analysis, improving the shade representation would enhance T-NET accuracy, especially for the maximum daily temperatures, which are currently not very well modelized. This study evaluates the most efficient way (accuracy/computing time) to improve the shade model thanks to 1-m resolution LIDAR data available on tributary of the LoireRiver (317 km long and an area of 8280 km²). Two methods are tested and compared: the first one is a spatially explicit computation of the cast shadow for every LIDAR pixel. The second is based on averaged vegetation cover characteristics of buffers and reaches of variable size. Validation of the water temperature model is made against 4 temperature sensors well spread along the stream, as well as two airborne thermal infrared imageries acquired in summer 2014 and winter 2015 over a 80 km reach. The poster will present the optimal length- and crosswise scale to characterize the vegetation from LIDAR data.

A national-scale remote sensing-based methodology for quantifying tidal marsh biomass to support "Blue Carbon" accounting

NASA Astrophysics Data System (ADS)

Byrd, K. B.; Ballanti, L.; Nguyen, D.; Simard, M.; Thomas, N.; Windham-Myers, L.; Castaneda, E.; Kroeger, K. D.; Gonneea, M. E.; O'Keefe Suttles, J.; Megonigal, P.; Troxler, T.; Schile, L. M.; Davis, M.; Woo, I.

2016-12-01

According to 2013 IPCC Wetlands Supplement guidelines, tidal marsh Tier 2 or Tier 3 accounting must include aboveground biomass carbon stock changes. To support this need, we are using free satellite and aerial imagery to develop a national scale, consistent remote sensing-based methodology for quantifying tidal marsh aboveground biomass. We are determining the extent to which additional satellite data will increase the accuracy of this "blue carbon" accounting. Working in 6 U.S. estuaries (Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA), we built a tidal marsh biomass dataset (n=2404). Landsat reflectance data were matched spatially and temporally with field plots using Google Earth Engine. We quantified percent cover of green vegetation, non-vegetation, and open water in Landsat pixels using segmentation of 1m National Agriculture Imagery Program aerial imagery. Sentinel-1A C-band backscatter data were used in Chesapeake, Mississippi Delta and Puget Sound. We tested multiple Landsat vegetation indices and Sentinel backscatter metrics in 30m scale biomass linear regression models by region. Scaling biomass by fraction green vegetation significantly improved biomass estimation (e.g. Cape Cod: R2 = 0.06 vs. R2 = 0.60, n=28). The best vegetation indices differed by region, though indices based on the shortwave infrared-1 and red bands were most predictive in the Everglades and the Mississippi Delta, while the soil adjusted vegetation index was most predictive in Puget Sound and Chesapeake. Backscatter metrics significantly improved model predictions over vegetation indices alone; consistently across regions, the most significant metric was the range in backscatter values within the green vegetation segment of the Landsat pixel (e.g. Mississippi Delta: R2 = 0.47 vs. R2 = 0.59, n=15). Results support using remote sensing of biomass stock change to estimate greenhouse gas emission factors in tidal wetlands.

Large scale track analysis for wide area motion imagery surveillance

NASA Astrophysics Data System (ADS)

van Leeuwen, C. J.; van Huis, J. R.; Baan, J.

2016-10-01

Wide Area Motion Imagery (WAMI) enables image based surveillance of areas that can cover multiple square kilometers. Interpreting and analyzing information from such sources, becomes increasingly time consuming as more data is added from newly developed methods for information extraction. Captured from a moving Unmanned Aerial Vehicle (UAV), the high-resolution images allow detection and tracking of moving vehicles, but this is a highly challenging task. By using a chain of computer vision detectors and machine learning techniques, we are capable of producing high quality track information of more than 40 thousand vehicles per five minutes. When faced with such a vast number of vehicular tracks, it is useful for analysts to be able to quickly query information based on region of interest, color, maneuvers or other high-level types of information, to gain insight and find relevant activities in the flood of information. In this paper we propose a set of tools, combined in a graphical user interface, which allows data analysts to survey vehicles in a large observed area. In order to retrieve (parts of) images from the high-resolution data, we developed a multi-scale tile-based video file format that allows to quickly obtain only a part, or a sub-sampling of the original high resolution image. By storing tiles of a still image according to a predefined order, we can quickly retrieve a particular region of the image at any relevant scale, by skipping to the correct frames and reconstructing the image. Location based queries allow a user to select tracks around a particular region of interest such as landmark, building or street. By using an integrated search engine, users can quickly select tracks that are in the vicinity of locations of interest. Another time-reducing method when searching for a particular vehicle, is to filter on color or color intensity. Automatic maneuver detection adds information to the tracks that can be used to find vehicles based on their behavior.

Surface-wave amplitude analysis for array data with non-linear waveform fitting: Toward high-resolution attenuation models of the upper mantle

NASA Astrophysics Data System (ADS)

Hamada, K.; Yoshizawa, K.

2013-12-01

Anelastic attenuation of seismic waves provides us with valuable information on temperature and water content in the Earth's mantle. While seismic velocity models have been investigated by many researchers, anelastic attenuation (or Q) models have yet to be investigated in detail mainly due to the intrinsic difficulties and uncertainties in the amplitude analysis of observed seismic waveforms. To increase the horizontal resolution of surface wave attenuation models on a regional scale, we have developed a new method of fully non-linear waveform fitting to measure inter-station phase velocities and amplitude ratios simultaneously, using the Neighborhood Algorithm (NA) as a global optimizer. Model parameter space (perturbations of phase speed and amplitude ratio) is explored to fit two observed waveforms on a common great-circle path by perturbing both phase and amplitude of the fundamental-mode surface waves. This method has been applied to observed waveform data of the USArray from 2007 to 2008, and a large-number of inter-station amplitude and phase speed data are corrected in a period range from 20 to 200 seconds. We have constructed preliminary phase speed and attenuation models using the observed phase and amplitude data, with careful considerations of the effects of elastic focusing and station correction factors for amplitude data. The phase velocity models indicate good correlation with the conventional tomographic results in North America on a large-scale; e.g., significant slow velocity anomaly in volcanic regions in the western United States. The preliminary results of surface-wave attenuation achieved a better variance reduction when the amplitude data are inverted for attenuation models in conjunction with corrections for receiver factors. We have also taken into account the amplitude correction for elastic focusing based on a geometrical ray theory, but its effects on the final model is somewhat limited and our attenuation model show anti-correlation with the phase velocity models; i.e., lower attenuation is found in slower velocity areas that cannot readily be explained by the temperature effects alone. Some former global scale studies (e.g., Dalton et al., JGR, 2006) indicated that the ray-theoretical focusing corrections on amplitude data tend to eliminate such anti-correlation of phase speed and attenuation, but this seems not to work sufficiently well for our regional scale model, which is affected by stronger velocity gradient relative to global-scale models. Thus, the estimated elastic focusing effects based on ray theory may be underestimated in our regional-scale studies. More rigorous ways to estimate the focusing corrections as well as data selection criteria for amplitude measurements are required to achieve a high-resolution attenuation models on regional scales in the future.

Preferential flow from pore to landscape scales

NASA Astrophysics Data System (ADS)

Koestel, J. K.; Jarvis, N.; Larsbo, M.

2017-12-01

In this presentation, we give a brief personal overview of some recent progress in quantifying preferential flow in the vadose zone, based on our own work and those of other researchers. One key challenge is to bridge the gap between the scales at which preferential flow occurs (i.e. pore to Darcy scales) and the scales of interest for management (i.e. fields, catchments, regions). We present results of recent studies that exemplify the potential of 3-D non-invasive imaging techniques to visualize and quantify flow processes at the pore scale. These studies should lead to a better understanding of how the topology of macropore networks control key state variables like matric potential and thus the strength of preferential flow under variable initial and boundary conditions. Extrapolation of this process knowledge to larger scales will remain difficult, since measurement technologies to quantify macropore networks at these larger scales are lacking. Recent work suggests that the application of key concepts from percolation theory could be useful in this context. Investigation of the larger Darcy-scale heterogeneities that generate preferential flow patterns at the soil profile, hillslope and field scales has been facilitated by hydro-geophysical measurement techniques that produce highly spatially and temporally resolved data. At larger regional and global scales, improved methods of data-mining and analyses of large datasets (machine learning) may help to parameterize models as well as lead to new insights into the relationships between soil susceptibility to preferential flow and site attributes (climate, land uses, soil types).