scholarly journals Comparing Evapotranspiration Products of Different Temporal and Spatial Scales in Native and Managed Prairie Pastures

2020 ◽  
Vol 13 (1) ◽  
pp. 82
Author(s):  
Rajen Bajgain ◽  
Xiangming Xiao ◽  
Pradeep Wagle ◽  
John S. Kimball ◽  
Colin Brust ◽  
...  
Keyword(s):  
Great Plains ◽  
Water Cycle ◽  
Spatial Scales ◽  
The United States ◽  
Vegetation Growth ◽  
Native Prairie ◽  
Differential Responses ◽  
Spatio Temporal ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference

Grasslands in the Southern Great Plains of the United States have major ecological and economic importance, with strong climate and water cycle connections. The historic native prairie grassland has been managed differently for enhancing productivity, while consequently altering water vapor fluxes. However, little is known about the impacts of different management activities on evapotranspiration (ET) at different spatio-temporal scales. In this study, we quantified and compared ET between co-located introduced managed pasture (MP) and native prairie (NP) pasture. Additionally, we compared the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived ET at four different spatial scales: 30 m (ETMOD30), 200 m (ETMOD200), 500 m (ETMOD500), and 1000 m (ETMOD1000) with eddy covariance-measured ET (ETEC). Large differences in ETEC were observed between two pastures from half-hourly to seasonal scales, with variations mainly controlled by the amount of rainfall and management activities. The results demonstrated differential responses of MP and NP in a pluvial year. The ETMOD30 showed a better agreement with ETEC than did the ETMOD200, ETMOD500, and ETMOD1000. The ETMOD200, ETMOD500, and ETMOD1000 largely underestimated ETEC, most likely due to their inability to capture the spatial heterogeneity of vegetation growth impacted by various management activities. Our results facilitate understanding of the difference in ET of MP and NP due to differences in vegetation resulting from different management activities and their differential responses to precipitation.

An Integrated Variational Framework for Mapping Evapotranspiration by Assimilating GOES LST and SMAP data

2020 ◽  
Author(s):  
Leila farhadi ◽  
Abedeh Abdolghafoorian
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Land Surface ◽  
Water Cycle ◽  
Spatial Scales ◽  
Coupled Model ◽  
Balance Model ◽  
Parameter Estimates ◽  
Dynamic Feedback ◽  
Unknown Parameters

<p>Evapotranspiration (ET) is a key component of terrestrial water cycle that plays an important role in the Earth system. Aaccurate estimation of ET is crucial in various hydrological, meteorological, and agricultural applications. In situ measurements of ET are costly and cannot be readily scaled to regional scales relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of ET using land surface state observations that are widely available from remote sensing across a range of spatial scales.</p><p>In this work, A variational data (VDA) assimilation framework is developed to estimate ET by assimilating Soil Moisture Active Passive (SMAP) soil moisture and Geostationary Operational Environmental Satellite (GOES) land surface temperature data into a coupled dual-source energy and water balance model.</p><p>The VDA framework estimates the key parameters of the coupled model, which regulate the partitioning of available energy (i.e., neutral bulk heat transfer coefficient (CH<sub>N</sub>) and evaporative fraction from soil (EF<sub>S</sub>) and canopy (EF<sub>C</sub>)). The uncertainties of the retrieved unknown parameters are estimated through the inverse of Hessian of cost function, obtained using the Lagrangian methodology. Analysis of the second-order information provides a tool to identify the optimum parameter estimates and guides towards a well-posed estimation problem.</p><p>The VDA framework is implemented over an area of 21780 km<sup>2</sup> in the U.S. Southern Great Plains (with computational grid size of 0.05 degree) during a nine-month period. The maps of retrieved evaporation and transpiration are used to study a number of dynamic feedback mechanisms between the land and atmosphere, such as the dependence of evapotranspiration on vegetation and soil moisture.</p>

Germination Ecology of Biennial Wormwood (Artemisia biennis) and Lanceleaf Sage (Salvia reflexa) Seeds

Weed Science ◽  
2010 ◽  
Vol 58 (1) ◽  
pp. 61-66 ◽  
Author(s):  
George O. Kegode ◽  
Gauri Nazre ◽  
Michael J. Christoffers
Keyword(s):  
Great Plains ◽  
Seed Viability ◽  
Field Studies ◽  
The United States ◽  
Northern Great Plains ◽  
Freezing And Thawing ◽  
Seed Decay ◽  
Soil Seedbank ◽  
The Difference ◽  
Fluctuating Temperatures

Biennial wormwood and lanceleaf sage have become serious weeds of several crops within the northern Great Plains of the United States and Canada. Both species are prolific seed producers but little is known about their potential for developing persistent seedbanks. Field studies were conducted to determine the influence of duration (7, 8, 11, 19, 20, and 23 mo) and depth of burial (0, 2.5, and 10 cm) on biennial wormwood and lanceleaf sage seed viability and decay. Biennial wormwood and lanceleaf sage seeds were buried in September 2003 (burial 1) and September 2004 (burial 2). In burial 1, biennial wormwood and lanceleaf sage seed viability was 65 and 66%, respectively, after 23 mo of burial. In burial 2, biennial wormwood and lanceleaf sage seed viability was 8 and 3%, respectively, after 23 mo of burial. The difference was likely because of higher soil moisture during burial 2, which promoted seed decay. Controlled-environment studies sought to determine the influence of stratification environments (freezing, chilling, and freeze–thaw) followed by exposure to diurnally fluctuating temperatures on germination of biennial wormwood and lanceleaf sage seeds. Stratified biennial wormwood seed germination was 95% or greater when incubated in fluctuating day/night temperatures of 37/20 or 37/25 C. Stratified lanceleaf sage seeds from freezing and chilling environments did not differ in germination following incubation in fluctuating temperatures and averaged 56 and 55%, respectively. Germination of stratified lanceleaf sage seeds from the freezing and thawing environment was higher than 50% during the thawing cycle, suggesting the possibility of early season emergence of this species. Our study indicates that biennial wormwood and lanceleaf sage have the potential to develop a seedbank that can persist for more than 2 yr. High moisture levels in the soil seedbank can lead to reduced seed survival.

scholarly journals Drought and Pluvial Dipole Events within the Great Plains of the United States

2015 ◽  
Vol 54 (9) ◽  
pp. 1886-1898 ◽  
Author(s):  
Jordan Christian ◽  
Katarina Christian ◽  
Jeffrey B. Basara
Keyword(s):  
United States ◽  
Standard Deviation ◽  
Great Plains ◽  
Spatial Scales ◽  
The United States ◽  
Northern Great Plains ◽  
High Plains ◽  
Southern Great Plains ◽  
One Year ◽  
The U.S

AbstractThe purpose of this study was to quantify dipole events (a drought year followed by a pluvial year) for various spatial scales including the nine Oklahoma climate divisions and the author-defined regions of the U.S. Southern Great Plains (SGP), High Plains (HP), and Northern Great Plains (NGP). Analyses revealed that, on average, over twice as many standard deviation (STDEV) dipoles existed in the latter half of the dataset (1955–2013) relative to the first half (1896–1954), suggesting that dramatic increases in precipitation from one year to the next within the Oklahoma climate divisions are increasing with time. For the larger regions within the Great Plains of the United States, the percent chance of a significant pluvial year following a significant drought year was approximately 25% of the time for the SGP and NGP and approximately 16% of the time for the HP. The STDEV dipole analyses further revealed that the frequency of dipoles was consistent between the first and second half of the dataset for the NGP and HP but was increasing with time in the SGP. The temporal periods of anomalous precipitation during relative pluvial years within the STDEV dipole events were unique for each region whereby October occurred most frequently (70%) within the SGP, September occurred most frequently (60%) within the HP, and May occurred most frequently (62%) within the NGP.

scholarly journals Spatio-temporal variability in growth of juvenile sparid fishes from the Mediterranean littoral zone

1999 ◽  
Vol 79 (1) ◽  
pp. 137-143 ◽  
Author(s):  
S. Planes ◽  
E. Macpherson ◽  
F. Biagi ◽  
A. Garcia-Rubies ◽  
J. Harmelin ◽  
...  
Keyword(s):  
Growth Rate ◽  
Spatial Scales ◽  
Western Mediterranean ◽  
Underwater Visual Census ◽  
Frequency Distributions ◽  
Diplodus Puntazzo ◽  
The North ◽  
Western Mediterranean Sea ◽  
Spatio Temporal ◽  
The Difference

Populations of three species of juvenile Sparidae (Diplodus puntazzo, Diplodus sargus and Diplodus vulgaris) were sampled at different spatial scales in the north-western Mediterranean Sea over two years to follow growth after settlement. Length–frequency distributions were collected each week for periods of six months following the arrival of off-shore larvae in inshore habitats. Data were collected by underwater visual census along permanent transects.Growth rate measured as the slope of the linear relationship between mean size and time varied between species. Diplodus puntazzo (0.160 mm d−1) and D. vulgaris (0.202 mm d−1), which are settling in winter experienced slower growth than D. sargus (0.567 mm d−1) which settles in summer. It is concluded that the difference was in part due to water temperature. Analysis of growth rate within each species also revealed significant differences among sites probably related to the currents and the water mass temperatures.

scholarly journals A Spatial Pattern Analysis of Land Surface Roughness Heterogeneity and its Relationship to the Initiation of Weak Tornadoes

2019 ◽  
Vol 23 (5) ◽  
pp. 1-28 ◽  
Author(s):  
Amanda Markert ◽  
Robert Griffin ◽  
Kevin Knupp ◽  
Andrew Molthan ◽  
Tim Coleman
Keyword(s):  
Surface Roughness ◽  
Great Plains ◽  
Land Surface ◽  
Spatial Scales ◽  
Land Surface Model ◽  
The United States ◽  
Surface Model ◽  
Spatial Pattern Analysis ◽  
Horizontal Gradients ◽  
Vorticity Vector

Abstract North Alabama is among the most tornado-prone regions in the United States and is composed of more spatially variable terrain and land cover than the frequently studied North American Great Plains region. Because of the high tornado frequency observed across north Alabama, there is a need to understand how land surface roughness heterogeneity influences tornadogenesis, particularly for weak-intensity tornadoes. This study investigates whether horizontal gradients in land surface roughness exist surrounding locations of tornadogenesis for weak (EF0–EF1) tornadoes. The existence of the horizontal gradients could lead to the generation of positive values of the vertical components of the 3D vorticity vector near the surface that may aid in the tornadogenesis process. In this study, surface roughness was estimated using parameterizations from the Noah land surface model with inputs from MODIS 500-m and Landsat 30-m data. Spatial variations in the parameterized roughness lengths were assessed using GIS-based grid and quadrant pattern analyses to quantify observed variation of land surface features surrounding tornadogenesis locations across spatial scales. This analysis determined that statistically significant horizontal gradients in surface roughness exist surrounding tornadogenesis locations.

scholarly journals MUSCAT: Multi-Scale Spatio-Temporal Learning with Application to Climate Modeling

2018 ◽  
Author(s):  
Jianpeng Xu ◽  
Xi Liu ◽  
Tyler Wilson ◽  
Pang-Ning Tan ◽  
Pouyan Hatami ◽  
...  
Keyword(s):  
Prediction Models ◽  
Learning Algorithm ◽  
Spatial Scales ◽  
The United States ◽  
Temporal Data ◽  
Real World Data ◽  
Temporal Prediction ◽  
Multi Scale ◽  
Temporal Models ◽  
Spatio Temporal

In climate and environmental sciences, vast amount of spatio-temporal data have been generated at varying spatial resolutions from satellite observations and computer models. Integrating such diverse sources of data has proven to be useful for building prediction models as the multi-scale data may capture different aspects of the Earth system. In this paper, we present a novel framework called MUSCAT for predictive modeling of multi-scale, spatio-temporal data. MUSCAT performs a joint decomposition of multiple tensors from different spatial scales, taking into account the relationships between the variables. The latent factors derived from the joint tensor decomposition are  used to train the spatial and temporal prediction models at different scales for each location. The outputs from these ensemble of spatial and temporal models will be aggregated to generate future predictions. An incremental learning algorithm is also proposed to handle the massive size of the tensors. Experimental results on real-world data from the United States Historical Climate Network (USHCN) showed that MUSCAT outperformed other competing methods in more than 70\% of the locations.

scholarly journals Comparison of Satellite and Drone-Based Images at Two Spatial Scales to Evaluate Vegetation Regeneration after Post-Fire Treatments in a Mediterranean Forest

2021 ◽  
Vol 11 (12) ◽  
pp. 5423
Author(s):  
Jose Luis Martinez ◽  
Manuel Esteban Lucas-Borja ◽  
Pedro Antonio Plaza-Alvarez ◽  
Pietro Denisi ◽  
Miguel Angel Moreno ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Spatial Scales ◽  
Soil Surface ◽  
Plant Biodiversity ◽  
Mediterranean Forests ◽  
Experimental Conditions ◽  
Vegetation Growth ◽  
Surface Conditions ◽  
Vegetation Regeneration ◽  
Forest Managers

The evaluation of vegetation cover after post-fire treatments of burned lands is important for forest managers to restore soil quality and plant biodiversity in burned ecosystems. Unfortunately, this evaluation may be time consuming and expensive, requiring much fieldwork for surveys. The use of remote sensing, which makes these evaluation activities quicker and easier, have rarely been carried out in the Mediterranean forests, subjected to wildfire and post-fire stabilization techniques. To fill this gap, this study evaluates the feasibility of satellite (using LANDSAT8 images) and drone surveys to evaluate changes in vegetation cover and composition after wildfire and two hillslope stabilization treatments (log erosion barriers, LEBs, and contour-felled log debris, CFDs) in a forest of Central Eastern Spain. Surveys by drone were able to detect the variability of vegetation cover among burned and unburned areas through the Visible Atmospherically Resistant Index (VARI), but gave unrealistic results when the effectiveness of a post-fire treatment must be evaluated. LANDSAT8 images may be instead misleading to evaluate the changes in land cover after wildfire and post-fire treatments, due to the lack of correlation between VARI and vegetation cover. The spatial analysis has shown that: (i) the post-fire restoration strategy of landscape managers that have prioritized steeper slopes for treatments was successful; (ii) vegetation growth, at least in the experimental conditions, played a limited influence on soil surface conditions, since no significant increases in terrain roughness were detected in treated areas.

scholarly journals Exploring the Use of PlanetScope Data for Particulate Matter Air Quality Research

2021 ◽  
Vol 13 (15) ◽  
pp. 2981
Author(s):  
Jeanné le Roux ◽  
Sundar Christopher ◽  
Manil Maskey
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Land Cover ◽  
Spectral Response ◽  
Fine Particulate Matter ◽  
Daily Basis ◽  
Land Cover Types ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Geolocation Accuracy

Planet, a commercial company, has achieved a key milestone by launching a large fleet of small satellites (smallsats) that provide high spatial resolution imagery of the entire Earth’s surface on a daily basis with its PlanetScope sensors. Given the potential utility of these data, this study explores the use for fine particulate matter (PM2.5) air quality applications. However, before these data can be utilized for air quality applications, key features of the data, including geolocation accuracy, calibration quality, and consistency in spectral signatures, need to be addressed. In this study, selected Dove-Classic PlanetScope data is screened for geolocation consistency. The spectral response of the Dove-Classic PlanetScope data is then compared to Moderate Resolution Imaging Spectroradiometer (MODIS) data over different land cover types, and under varying PM2.5 and mid visible aerosol optical depth (AOD) conditions. The data selected for this study was found to fall within Planet’s reported geolocation accuracy of 10 m (between 3–4 pixels). In a comparison of top of atmosphere (TOA) reflectance over a sample of different land cover types, the difference in reflectance between PlanetScope and MODIS ranged from near-zero (0.0014) to 0.117, with a mean difference in reflectance of 0.046 ± 0.031 across all bands. The reflectance values from PlanetScope were higher than MODIS 78% of the time, although no significant relationship was found between surface PM2.5 or AOD and TOA reflectance for the cases that were studied. The results indicate that commercial satellite data have the potential to address Earth-environmental issues.

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