Extreme drought effects on summer evapotranspiration and energy balance of a grassland in the Southern Great Plains

Ecohydrology ◽  
2014 ◽  
Vol 8 (7) ◽  
pp. 1194-1204 ◽  
Author(s):  
Nithya Rajan ◽  
Stephan J. Maas ◽  
Song Cui
Keyword(s):  
Energy Balance ◽  
Great Plains ◽  
Extreme Drought ◽  
Southern Great Plains ◽  
Drought Effects

scholarly journals Soil Moisture, Grass Production and Mesquite Resprout Architecture Following Mesquite Above-Ground Mortality

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1243 ◽  
Author(s):  
R. Ansley ◽  
Tian Zhang ◽  
Caitlyn Cooper
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Plant Root ◽  
Perennial Grass ◽  
Extreme Drought ◽  
Negative Consequences ◽  
North Central ◽  
Southern Great Plains ◽  
Grass Production ◽  
Central Texas

Honey mesquite (Prosopis glandulosa) is an invasive native woody plant in the southern Great Plains, USA. Treatments used to slow the invasion rate have either killed the plant (“root-kill”) or killed above-ground tissue (“top-kill”). Top-killing provides temporary suppression, but stimulates multi-stemmed regrowth. This study from north central Texas quantified soil moisture, grass production and mesquite resprout architecture following a mechanical clearing treatment that top-killed mesquite (cleared) compared to untreated mesquite woodland (woodland) over a 10-year period. During an extreme drought at 5 and 6 years post-clearing, soil moisture at 60-cm depth became lower in cleared than in woodland, suggesting that, as early as 5 years after top-kill, water use by regrowth mesquite could be greater than that by woodland mesquite. Perennial grass production was greater in cleared treatments than in woodland treatments in all years except the extreme drought years. Mesquite regrowth biomass increased numerically each year and was independent of annual precipitation with one exception. During the year 5 and 6 drought, mesquite stopped lateral expansion of larger stems and increased growth of smaller stems and twigs. In summary, top-killing mesquite generated short-term benefits of increased grass production, but regrowth created potentially negative consequences related to soil moisture.

Modeling Evapotranspiration of Winter Wheat Using Contextual and Pixel-Based Surface Energy Balance Models

2021 ◽  
Vol 64 (2) ◽  
pp. 507-519
Author(s):  
Kul Khand ◽  
Nishan Bhattarai ◽  
Saleh Taghvaeian ◽  
Pradeep Wagle ◽  
Prasanna H. Gowda ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Winter Wheat ◽  
Great Plains ◽  
Surface Energy Balance ◽  
List Type ◽  
Landsat Images ◽  
Practical Applications ◽  
Southern Great Plains ◽  
Flux Tower

HighlightsThree contextual-based (CB) and two pixel-based (PB) models were evaluated to estimate ET of rainfed winter wheat.Instantaneous available energy estimation and ET upscaling impacted model performance.The CB models performed better at instantaneous and daily scales compared to the PB models.ET estimation biases increased during low vegetation and drier conditions, especially for the PB models.Abstract. Surface energy balance (SEB) models based on thermal remote sensing data are widely used in research applications to map evapotranspiration (ET) across various landscapes. However, their ability to capture ET from winter wheat remains underexplored, especially in practical applications such as integrated resource management and drought preparedness. Investigating winter wheat ET dynamics is important in agricultural regions such as the Southern Great Plains of the U.S., where winter wheat is extensively cultivated. The goal of this study was to evaluate the performance of five fully automated SEB models, three contextual-based (CB) and two pixel-based (PB), in estimating instantaneous and daily ET of winter wheat by comparing the model results with flux tower observations. The CB models included Surface Energy Balance Algorithm for Land (SEBAL), Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC), and Triangular Vegetation Temperature (TVT). The PB models included Surface Energy Balance System (SEBS) and Two-Source Energy Balance (TSEB). Model evaluation during two winter wheat growing seasons (2016-2018) using 28 Landsat images showed that the instantaneous ET estimates from METRIC and TSEB had the smallest (RMSE = 0.14 mm h-1) and largest (RMSE = 0.27 mm h-1) errors, respectively. At the daily scale, SEBAL was the best performing model (RMSE = 1.0 mm d-1), followed by TVT (RMSE = 1.1 mm d-1), METRIC (RMSE = 1.2 mm d-1), SEBS (RMSE = 1.3 mm d-1), and TSEB (RMSE = 1.5 mm d-1). Overall, the CB models provided smaller errors than the PB models. Larger errors in daily ET estimation were observed during low vegetation and drier conditions, especially for the PB models. Keywords: Flux tower, Landsat, Southern Great Plains, Water use.

Seasonal and interannual variability in13C composition of ecosystem carbon fluxes in the U.S. Southern Great Plains

Tellus B ◽  
2011 ◽  
Vol 63 (2) ◽  
Author(s):  
Margaret S. Torn ◽  
Sebastien C. Biraud ◽  
Christopher J. Still ◽  
William J. Riley ◽  
Joe A. Berry
Keyword(s):  
Interannual Variability ◽  
Great Plains ◽  
Carbon Fluxes ◽  
Southern Great Plains ◽  
Seasonal And Interannual Variability ◽  
Ecosystem Carbon ◽  
Ecosystem Carbon Fluxes ◽  
The U.S

scholarly journals Vulnerability of crops and native grasses to summer drying in the U.S. Southern Great Plains

2015 ◽  
Vol 213 ◽  
pp. 209-218 ◽  
Author(s):  
Naama Raz-Yaseef ◽  
Dave P. Billesbach ◽  
Marc L. Fischer ◽  
Sebastien C. Biraud ◽  
Stacey A. Gunter ◽  
...  
Keyword(s):  
Great Plains ◽  
Native Grasses ◽  
Southern Great Plains ◽  
The U.S

The Impact of Affective Heuristics in Decision-Making Regarding the Implementation of Prescribed Fire on Private Rangelands in the Southern Great Plains, USA

2021 ◽  
pp. 1-18
Author(s):  
J. Kelly Hoffman ◽  
R. Patrick Bixler ◽  
Morgan L. Treadwell ◽  
Lars G. Coleman ◽  
Thomas W. McDaniel ◽  
...  
Keyword(s):  
Decision Making ◽  
Great Plains ◽  
Prescribed Fire ◽  
Southern Great Plains ◽  
The Impact

scholarly journals Summertime Continental Shallow Cumulus Cloud Detection Using GOES-16 Satellite and Ground-Based Stereo Cameras at the DOE ARM Southern Great Plains Site

2021 ◽  
Vol 13 (12) ◽  
pp. 2309
Author(s):  
Jingjing Tian ◽  
Yunyan Zhang ◽  
Stephen A. Klein ◽  
Likun Wang ◽  
Rusen Öktem ◽  
...  
Keyword(s):  
Great Plains ◽  
Land Surface ◽  
Detection Threshold ◽  
Department Of Energy ◽  
Surface Reflectance ◽  
Cloud Detection ◽  
Southern Great Plains ◽  
Clear Sky ◽  
Shallow Cumulus ◽  
Stereo Cameras

Summertime continental shallow cumulus clouds (ShCu) are detected using Geostationary Operational Environmental Satellite (GOES)-16 reflectance data, with cross-validation by observations from ground-based stereo cameras at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. A ShCu cloudy pixel is identified when the GOES reflectance exceeds the clear-sky surface reflectance by a reflectance detection threshold of ShCu, ΔR. We firstly construct diurnally varying clear-sky surface reflectance maps and then estimate the ∆R. A GOES simulator is designed, projecting the clouds reconstructed by stereo cameras towards the surface along the satellite’s slanted viewing direction. The dynamic ShCu detection threshold ΔR is determined by making the GOES cloud fraction (CF) equal to the CF from the GOES simulator. Although there are temporal variabilities in ΔR, cloud fractions and cloud size distributions can be well reproduced using a constant ΔR value of 0.045. The method presented in this study enables daytime ShCu detection, which is usually falsely reported as clear sky in the GOES-16 cloud mask data product. Using this method, a new ShCu dataset can be generated to bridge the observational gap in detecting ShCu, which may transition into deep precipitating clouds, and to facilitate further studies on ShCu development over heterogenous land surface.

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