A Five-Year Evaluation of SMOS Level 2 Soil Moisture in the Corn Belt of the United States

2018 ◽  
Vol 11 (12) ◽  
pp. 4664-4675 ◽  
Author(s):  
Victoria A. Walker ◽  
Brian K. Hornbuckle ◽  
Michael H. Cosh
Keyword(s):  
United States ◽  
Soil Moisture ◽  
The United States ◽  
Corn Belt ◽  
Level 2

scholarly journals The Polarimetric Sensitivity of SMAP-Reflectometry Signals to Crop Growth in the U.S. Corn Belt

2020 ◽  
Vol 12 (6) ◽  
pp. 1007
Author(s):  
Nereida Rodriguez-Alvarez ◽  
Sidharth Misra ◽  
Mary Morris
Keyword(s):  
United States ◽  
Soil Moisture ◽  
The United States ◽  
Crop Growth ◽  
Corn Belt ◽  
Retrieval Algorithm ◽  
Agricultural Crop ◽  
Crop Height ◽  
Crop Type ◽  
The Impact

Crop growth is an important parameter to monitor in order to obtain accurate remotely sensed estimates of soil moisture, as well as assessments of crop health, productivity, and quality commonly used in the agricultural industry. The Soil Moisture Active Passive (SMAP) mission has been collecting Global Positioning System (GPS) signals as they reflect off the Earth’s surface since August 2015. The L-band dual-polarization reflection measurements enable studies of the evolution of geophysical parameters during seasonal transitions. In this paper, we examine the sensitivity of SMAP-reflectometry signals to agricultural crop growth related characteristics: crop type, vegetation water content (VWC), crop height, and vegetation opacity (VOP). The study presented here focuses on the United States “Corn Belt,” where an extensive area is planted every year with mostly corn, soybean, and wheat. We explore the potential to generate regularly an alternate source of crop growth information independent of the data currently used in the soil moisture (SM) products developed with the SMAP mission. Our analysis explores the variability of the polarimetric ratio (PR), computed from the peak signals at V- and H-polarization, during the United States Corn Belt crop growing season in 2017. The approach facilitates the understanding of the evolution of the observed surfaces from bare soil to peak growth and the maturation of the crops until harvesting. We investigate the impact of SM on PR for low roughness scenes with low variability and considering each crop type independently. We analyze the sensitivity of PR to the selected crop height, VWC, VOP, and Normalized Differential Vegetation Index (NDVI) reference datasets. Finally, we discuss a possible path towards a retrieval algorithm based on Global Navigation Satellite System-Reflectometry (GNSS-R) measurements that could be used in combination with passive SMAP soil moisture algorithms to correct simultaneously for the VWC and SM effects on the electromagnetic signals.

scholarly journals Assessing Disaggregated SMAP Soil Moisture Products in the United States

2021 ◽  
Vol 14 ◽  
pp. 2577-2592
Author(s):  
Pang-Wei Liu ◽  
Rajat Bindlish ◽  
Bin Fang ◽  
Venkat Lakshmi ◽  
Peggy E. O'Neill ◽  
...  
Keyword(s):  
United States ◽  
Soil Moisture ◽  
The United States

Assess 21st century Flash Drought in the United States using high resolution regional climate models

2021 ◽  
Author(s):  
Brandi Gamelin ◽  
Jiali Wang ◽  
V. Rao Kotamarthi
Keyword(s):  
Climate Change ◽  
United States ◽  
Soil Moisture ◽  
Climate Models ◽  
Wrf Model ◽  
The United States ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Regional Variability ◽  
Groundwater Levels

<p>Flash droughts are the rapid intensification of drought conditions generally associated with increased temperatures and decreased precipitation on short time scales.  Consequently, flash droughts are responsible for reduced soil moisture which contributes to diminished agricultural yields and lower groundwater levels. Drought management, especially flash drought in the United States is vital to address the human and economic impact of crop loss, diminished water resources and increased wildfire risk. In previous research, climate change scenarios show increased growing season (i.e. frost-free days) and drying in soil moisture over most of the United States by 2100. Understanding projected flash drought is important to assess regional variability, frequency and intensity of flash droughts under future climate change scenarios. Data for this work was produced with the Weather Research and Forecasting (WRF) model. Initial and boundary conditions for the model were supplied by CCSM4, GFDL-ESM2G, and HadGEM2-ES and based on the 8.5 Representative Concentration Pathway (RCP8.5). The WRF model was downscaled to a 12 km spatial resolution for three climate time frames: 1995-2004 (Historical), 2045-2054 (Mid), and 2085-2094 (Late).  A key characteristic of flash drought is the rapid onset and intensification of dry conditions. For this, we identify onset with vapor pressure deficit during each time frame. Known flash drought cases during the Historical run are identified and compared to flash droughts in the Mid and Late 21<sup>st</sup> century.</p>

scholarly journals The Impact of SMOS Soil Moisture Data Assimilation within the Operational Global Flood Awareness System (GloFAS)

2020 ◽  
Vol 12 (9) ◽  
pp. 1490 ◽  
Author(s):  
Calum Baugh ◽  
Patricia de Rosnay ◽  
Heather Lawrence ◽  
Toni Jurlina ◽  
Matthias Drusch ◽  
...  
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Data Assimilation ◽  
The United States ◽  
Streamflow Prediction ◽  
Soil Moisture Data ◽  
Skill Scores ◽  
High Flows ◽  
The Impact ◽  
Awareness System

In this study the impacts of Soil Moisture and Ocean Salinity (SMOS) soil moisture data assimilation upon the streamflow prediction of the operational Global Flood Awareness System (GloFAS) were investigated. Two GloFAS experiments were performed, one which used hydro-meteorological forcings produced with the assimilation of the SMOS data, the other using forcings which excluded the assimilation of the SMOS data. Both sets of experiment results were verified against streamflow observations in the United States and Australia. Skill scores were computed for each experiment against the observation datasets, the differences in the skill scores were used to identify where GloFAS skill may be affected by the assimilation of SMOS soil moisture data. In addition, a global assessment was made of the impact upon the 5th and 95th GloFAS flow percentiles to see how SMOS data assimilation affected low and high flows respectively. Results against in-situ observations found that GloFAS skill score was only affected by a small amount. At a global scale, the results showed a large impact on high flows in areas such as the Hudson Bay, central United States, the Sahel and Australia. There was no clear spatial trend to these differences as opposing signs occurred within close proximity to each other. Investigating the differences between the simulations at individual gauging stations showed that they often only occurred during a single flood event; for the remainder of the simulation period the experiments were almost identical. This suggests that SMOS data assimilation may affect the generation of surface runoff during high flow events, but may have less impact on baseflow generation during the remainder of the hydrograph. To further understand this, future work could assess the impact of SMOS data assimilation upon specific hydrological components such as surface and subsurface runoff.

scholarly journals Active-Optical Reflectance Sensing Corn Algorithms Evaluated over the United States Midwest Corn Belt

2018 ◽  
Vol 110 (6) ◽  
pp. 2552-2565 ◽  
Author(s):  
G. M. Bean ◽  
N. R. Kitchen ◽  
J. J. Camberato ◽  
R. B. Ferguson ◽  
F. G. Fernandez ◽  
...  
Keyword(s):  
United States ◽  
The United States ◽  
Corn Belt ◽  
Optical Reflectance

Agricultural pests consumed by common bat species in the United States corn belt: The importance of DNA primer choice

2020 ◽  
Vol 303 ◽  
pp. 107105
Author(s):  
Michael D. Whitby ◽  
Troy J. Kieran ◽  
Travis C. Glenn ◽  
Craig Allen
Keyword(s):  
United States ◽  
The United States ◽  
Corn Belt ◽  
Agricultural Pests

scholarly journals A Methodology for Flash Drought Identification: Application of Flash Drought Frequency across the United States

2019 ◽  
Vol 20 (5) ◽  
pp. 833-846 ◽  
Author(s):  
Jordan I. Christian ◽  
Jeffrey B. Basara ◽  
Jason A. Otkin ◽  
Eric D. Hunt ◽  
Ryann A. Wakefield ◽  
...  
Keyword(s):  
United States ◽  
Great Lakes ◽  
Great Plains ◽  
Hot Spot ◽  
The United States ◽  
General Definition ◽  
Corn Belt ◽  
Great Lakes Region ◽  
Rapid Rate ◽  
Western Great Lakes

Abstract With the increasing use of the term “flash drought” within the scientific community, Otkin et al. provide a general definition that identifies flash droughts based on their unusually rapid rate of intensification. This study presents an objective percentile-based methodology that builds upon that work by identifying flash droughts using standardized evaporative stress ratio (SESR) values and changes in SESR over some period of time. Four criteria are specified to identify flash droughts: two that emphasize the vegetative impacts of flash drought and two that focus on the rapid rate of intensification. The methodology was applied to the North American Regional Reanalysis (NARR) to develop a 38-yr flash drought climatology (1979–2016) across the United States. It was found that SESR derived from NARR data compared well with the satellite-based evaporative stress index for four previously identified flash drought events. Furthermore, four additional flash drought cases were compared with the U.S. Drought Monitor (USDM), and SESR rapidly declined 1–2 weeks before a response was evident with the USDM. From the climatological analysis, a hot spot of flash drought occurrence was revealed over the Great Plains, the Corn Belt, and the western Great Lakes region. Relatively few flash drought events occurred over mountainous and arid regions. Flash droughts were categorized based on their rate of intensification, and it was found that the most intense flash droughts occurred over the central Great Plains, Corn Belt, and western Great Lakes region.

scholarly journals A Radar-Based Climatology of Mesoscale Convective Systems in the United States

2019 ◽  
Vol 32 (5) ◽  
pp. 1591-1606 ◽  
Author(s):  
Alex M. Haberlie ◽  
Walker S. Ashley
Keyword(s):  
United States ◽  
Agricultural Land ◽  
Gulf Coast ◽  
Warm Season ◽  
The United States ◽  
Corn Belt ◽  
High Plains ◽  
Convective System ◽  
Aquifer Recharge ◽  
Mesoscale Convective

Abstract This research applies an automated mesoscale convective system (MCS) segmentation, classification, and tracking approach to composite radar reflectivity mosaic images that cover the contiguous United States (CONUS) and span a relatively long study period of 22 years (1996–2017). These data afford a novel assessment of the seasonal and interannual variability of MCSs. Additionally, hourly precipitation data from 16 of those years (2002–17) are used to systematically examine rainfall associated with radar-derived MCS events. The attributes and occurrence of MCSs that pass over portions of the CONUS east of the Continental Divide (ECONUS), as well as five author-defined subregions—North Plains, High Plains, Corn Belt, Northeast, and Mid-South—are also examined. The results illustrate two preferred regions for MCS activity in the ECONUS: 1) the Mid-South and Gulf Coast and 2) the Central Plains and Midwest. MCS occurrence and MCS rainfall display a marked seasonal cycle, with most of the regions experiencing these events primarily during the warm season (May–August). Additionally, MCS rainfall was responsible for over 50% of annual and seasonal rainfall for many locations in the ECONUS. Of particular importance, the majority of warm-season rainfall for regions with high agricultural land use (Corn Belt) and important aquifer recharge properties (High Plains) is attributable to MCSs. These results reaffirm that MCSs are a significant aspect of the ECONUS hydroclimate.

Sign in / Sign up

Export Citation Format

Share Document